diff --git a/spatial_simulators/v0.0.1-rc1/dataset_info.json b/spatial_simulators/v0.0.1-rc1/dataset_info.json
new file mode 100644
index 0000000..bbf08fe
--- /dev/null
+++ b/spatial_simulators/v0.0.1-rc1/dataset_info.json
@@ -0,0 +1,182 @@
+[
+  {
+    "name": "osteosarcoma",
+    "label": "Osteosarcoma",
+    "commit": "missing-sha",
+    "summary": "Spatial profiling of human osteosarcoma cells.",
+    "description": "Spatial transcriptome profiling by MERFISH reveals subcellular RNA compartmentalization and cell cycle-dependent gene expression.",
+    "source_urls": ["https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE176078"],
+    "common_dataset_names": null,
+    "modalities": [],
+    "organisms": ["homo_sapiens"],
+    "authors": [],
+    "references": {
+      "doi": ["10.1073/pnas.1912459116"],
+      "bibtex": []
+    },
+    "date_created": "23-06-2026",
+    "file_size_mb": 20.1056
+  },
+  {
+    "name": "cortex",
+    "label": "Cortex",
+    "commit": "missing-sha",
+    "summary": "Scripts and source data for image processing, barcode calling, and cell type annotations in a seqFISH+ experiment.",
+    "description": "The dataset includes processed image data, cell type annotations with Louvain clusters, gene IDs for transcript locations, and mRNA point locations, with additional data available on Zenodo.",
+    "source_urls": ["https://zenodo.org/records/2669683"],
+    "common_dataset_names": null,
+    "modalities": [],
+    "organisms": ["homo_sapiens"],
+    "authors": [],
+    "references": {
+      "doi": ["10.1038/s41586-019-1049-y"],
+      "bibtex": []
+    },
+    "date_created": "23-06-2026",
+    "file_size_mb": 19.3329
+  },
+  {
+    "name": "breast",
+    "label": "Breast",
+    "commit": "missing-sha",
+    "summary": "A spatially resolved atlas of human breast cancers",
+    "description": "This study presents a spatially resolved transcriptomics analysis of human breast cancers.",
+    "source_urls": ["https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE176078"],
+    "common_dataset_names": null,
+    "modalities": [],
+    "organisms": ["homo_sapiens"],
+    "authors": [],
+    "references": {
+      "doi": ["10.1038/s41588-021-00911-1"],
+      "bibtex": []
+    },
+    "date_created": "23-06-2026",
+    "file_size_mb": 22.6482
+  },
+  {
+    "name": "prostate",
+    "label": "Prostate",
+    "commit": "missing-sha",
+    "summary": "Spatially resolved gene expression of human protate tissue slices treated with steroid hormones for 8 hours",
+    "description": "Spatially resolved gene expression was prepard by dissociated hman prostate tissue to single cells, and collected & prepped for RNA-seq using the Visium Spatial Gene Expression kit.",
+    "source_urls": ["https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE159697"],
+    "common_dataset_names": null,
+    "modalities": [],
+    "organisms": ["homo_sapiens"],
+    "authors": [],
+    "references": {
+      "doi": ["10.1016/j.isci.2021.102640"],
+      "bibtex": []
+    },
+    "date_created": "23-06-2026",
+    "file_size_mb": 19.6893
+  },
+  {
+    "name": "gastrulation",
+    "label": "Gastrulation",
+    "commit": "missing-sha",
+    "summary": "single-cell and spatial transcriptomic molecular map of mouse gastrulation",
+    "description": "Single-Cell omics Data across Mouse Gastrulation and Highly multiplexed spatially resolved gene expression profiling of Early Organogenesis.",
+    "source_urls": ["https://content.cruk.cam.ac.uk/jmlab/SpatialMouseAtlas2020/"],
+    "common_dataset_names": null,
+    "modalities": [],
+    "organisms": ["mus_musculus"],
+    "authors": [],
+    "references": {
+      "doi": ["10.1038/s41587-021-01006-2"],
+      "bibtex": []
+    },
+    "date_created": "23-06-2026",
+    "file_size_mb": 14.9637
+  },
+  {
+    "name": "brain",
+    "label": "Brain",
+    "commit": "missing-sha",
+    "summary": "10X Visium spatial RNA-seq from adult mouse brain sections paired to single-nucleus RNA-seq",
+    "description": "This datasets were generated matched single nucleus (sn, this submission) and Visium spatial RNA-seq (10X Genomics) profiles of adjacent mouse brain sections that contain multiple regions from the telencephalon and diencephalon.",
+    "source_urls": ["https://github.com/BayraktarLab/cell2location"],
+    "common_dataset_names": null,
+    "modalities": [],
+    "organisms": ["homo_sapiens"],
+    "authors": [],
+    "references": {
+      "doi": ["10.1038/s41587-021-01139-4"],
+      "bibtex": []
+    },
+    "date_created": "23-06-2026",
+    "file_size_mb": 42.6133
+  },
+  {
+    "name": "pdac",
+    "label": "pancreatic ductal adenocarcinomas",
+    "commit": "missing-sha",
+    "summary": "Integrating microarray-based spatial transcriptomics and single-cell RNA-seq reveals tissue architecture in pancreatic ductal adenocarcinomas",
+    "description": "We developed a multimodal intersection analysis method combining scRNA-seq with spatial transcriptomics to map and characterize the spatial organization and interactions of distinct cell subpopulations in complex tissues, such as primary pancreatic tumors..",
+    "source_urls": ["https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE111672"],
+    "common_dataset_names": null,
+    "modalities": [],
+    "organisms": ["homo_sapiens"],
+    "authors": [],
+    "references": {
+      "doi": ["10.1101/2020.12.01.407460"],
+      "bibtex": []
+    },
+    "date_created": "23-06-2026",
+    "file_size_mb": 17.5534
+  },
+  {
+    "name": "olfactorybulb",
+    "label": "Olfactorybulb",
+    "commit": "missing-sha",
+    "summary": "Single-cell and spatial transcriptomic of mouse olfactory bulb",
+    "description": "Single-cell and spatial transcriptomic of mouse olfactory bulb",
+    "source_urls": ["http://ww1.spatialtranscriptomicsresearch.org/?usid=24&utid=8672855942"],
+    "common_dataset_names": null,
+    "modalities": [],
+    "organisms": ["mus_musculus"],
+    "authors": [],
+    "references": {
+      "doi": ["10.1126/science.aaf2403"],
+      "bibtex": []
+    },
+    "date_created": "23-06-2026",
+    "file_size_mb": 2.2329
+  },
+  {
+    "name": "fibrosarcoma",
+    "label": "Fibrosarcoma",
+    "commit": "missing-sha",
+    "summary": "Multi-resolution deconvolution of spatial transcriptomics data reveals continuous patterns of Tumor A1 of Tissue 1",
+    "description": "Spatial transcriptomics of Tumor A1 of Tissue 1.",
+    "source_urls": ["https://github.com/romain-lopez/DestVI-reproducibility"],
+    "common_dataset_names": null,
+    "modalities": [],
+    "organisms": ["mus_musculus"],
+    "authors": [],
+    "references": {
+      "doi": ["10.1038/s41587-022-01272-8"],
+      "bibtex": []
+    },
+    "date_created": "23-06-2026",
+    "file_size_mb": 27.1576
+  },
+  {
+    "name": "hindlimbmuscle",
+    "label": "Hindlimbmuscle",
+    "commit": "missing-sha",
+    "summary": "Spatial RNA sequencing of regenerating mouse hindlimb muscle",
+    "description": "The spatial transcriptomics datasets regenerates mouse muscle tissue generated with the 10x Genomics Visium platform.",
+    "source_urls": ["https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE161318"],
+    "common_dataset_names": null,
+    "modalities": [],
+    "organisms": ["mus_musculus"],
+    "authors": [],
+    "references": {
+      "doi": ["10.1101/2020.12.01.407460"],
+      "bibtex": []
+    },
+    "date_created": "23-06-2026",
+    "file_size_mb": 19.1576
+  }
+]
diff --git a/spatial_simulators/v0.0.1-rc1/method_info.json b/spatial_simulators/v0.0.1-rc1/method_info.json
new file mode 100644
index 0000000..787f342
--- /dev/null
+++ b/spatial_simulators/v0.0.1-rc1/method_info.json
@@ -0,0 +1,211 @@
+[
+  {
+    "name": "scdesign2",
+    "label": "scDesign2",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "A transparent simulator that generates high-fidelity single-cell gene expression count data with gene correlations captured",
+    "description": "scDesign2 is a transparent simulator that achieves all three goals (preserving genes, capturing gene correlations, and generating any \nnumber of cells with varying sequencing depths) and generates high-fidelity synthetic data for multiple single-cell gene expression \ncount-based technologies.",
+    "type": "method",
+    "link_code": "https://github.com/JSB-UCLA/scDesign2",
+    "link_documentation": "https://htmlpreview.github.io/?https://github.com/JSB-UCLA/scDesign2/blob/master/vignettes/scDesign2.html",
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/methods/scdesign2",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/methods/scdesign2:build_main",
+    "authors": [],
+    "references": {
+      "doi": ["10.1186/s13059-021-02367-2"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "scdesign3_nb",
+    "label": "scDesign3 (NB)",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "A probabilistic model that unifies the generation and inference for single-cell and spatial omics data",
+    "description": "scDesign3 offers a probabilistic model that unifies the generation and inference\nfor single-cell and spatial omics data. The model's interpretable parameters and\nlikelihood enable scDesign3 to generate customized in silico data and unsupervisedly\nassess the goodness-of-fit of inferred cell latent structures (for example, clusters,\ntrajectories and spatial locations).",
+    "type": "method",
+    "link_code": "https://github.com/SONGDONGYUAN1994/scDesign3",
+    "link_documentation": "https://www.bioconductor.org/packages/release/bioc/html/scDesign3.html",
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/methods/scdesign3_nb",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/methods/scdesign3_nb:build_main",
+    "authors": [],
+    "references": {
+      "doi": ["10.1038/s41587-023-01772-1"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "scdesign3_poisson",
+    "label": "scDesign3 (Poisson)",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "A probabilistic model that unifies the generation and inference for single-cell and spatial omics data",
+    "description": "scDesign3 offers a probabilistic model that unifies the generation and inference\nfor single-cell and spatial omics data. The model's interpretable parameters and\nlikelihood enable scDesign3 to generate customized in silico data and unsupervisedly\nassess the goodness-of-fit of inferred cell latent structures (for example, clusters,\ntrajectories and spatial locations).",
+    "type": "method",
+    "link_code": "https://github.com/SONGDONGYUAN1994/scDesign3",
+    "link_documentation": "https://www.bioconductor.org/packages/release/bioc/html/scDesign3.html",
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/methods/scdesign3_poisson",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/methods/scdesign3_poisson:build_main",
+    "authors": [],
+    "references": {
+      "doi": ["10.1038/s41587-023-01772-1"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "sparsim",
+    "label": "SPARsim",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "SPARSim single cell is a count data simulator for scRNA-seq data.",
+    "description": "SPARSim is a scRNA-seq count data simulator based on a Gamma-Multivariate Hypergeometric model. \nIt allows to generate count data that resembles real data in terms of count intensity, variability and sparsity.",
+    "type": "method",
+    "link_code": "https://gitlab.com/sysbiobig/sparsim",
+    "link_documentation": "https://gitlab.com/sysbiobig/sparsim/-/blob/master/vignettes/sparsim.Rmd",
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/methods/sparsim",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/methods/sparsim:build_main",
+    "authors": [],
+    "references": {
+      "doi": ["10.1093/bioinformatics/btz752"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "splatter",
+    "label": "Splatter",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "A single cell RNA-seq data simulator based on a gamma-Poisson distribution.",
+    "description": "The Splat model is a gamma-Poisson distribution used to generate a gene by cell matrix of counts. Mean expression levels for each gene are simulated from a gamma distribution and the Biological Coefficient of Variation is used to enforce a mean-variance trend before counts are simulated from a Poisson distribution.",
+    "type": "method",
+    "link_code": "https://github.com/Oshlack/splatter",
+    "link_documentation": "https://bioconductor.org/packages/release/bioc/vignettes/splatter/inst/doc/splatter.html",
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/methods/splatter",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/methods/splatter:build_main",
+    "authors": [],
+    "references": {
+      "doi": ["10.1186/s13059-017-1305-0"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "srtsim",
+    "label": "SRTsim",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "An SRT-specific simulator for scalable, reproducible, and realistic SRT simulations.",
+    "description": "A key benefit of srtsim is its ability to maintain location-wise and gene-wise SRT count properties and \npreserve spatial expression patterns, enabling evaluation of SRT method performance using synthetic data.",
+    "type": "method",
+    "link_code": "https://github.com/xzhoulab/srtsim",
+    "link_documentation": "https://xzhoulab.github.io/SRTsim",
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/methods/srtsim",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/methods/srtsim:build_main",
+    "authors": [],
+    "references": {
+      "doi": ["10.1186/s13059-023-02879-z"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "symsim",
+    "label": "symsim",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "Simulating multiple faceted variability in single cell RNA sequencing",
+    "description": "SymSim is a simulator for modeling single-cell RNA-Seq data, accounting for three primary sources of variation: intrinsic transcription noise, extrinsic variation from different cell states, \nand technical variation from measurement noise and bias.",
+    "type": "method",
+    "link_code": "https://github.com/YosefLab/SymSim",
+    "link_documentation": "https://github.com/YosefLab/SymSim/blob/master/vignettes/SymSimTutorial.Rmd",
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/methods/symsim",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/methods/symsim:build_main",
+    "authors": [],
+    "references": {
+      "doi": ["10.1038/s41467-019-10500-w"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "zinbwave",
+    "label": "zinbwave",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "A general and flexible method for signal extraction from single-cell RNA-seq data",
+    "description": "ZINB-WaVE is a general and flexible zero-inflated negative binomial model, which leads to low-dimensional representations \nof the data that account for zero inflation (dropouts), over-dispersion, and the count nature of the data.",
+    "type": "method",
+    "link_code": "https://github.com/drisso/zinbwave",
+    "link_documentation": "https://bioconductor.org/packages/release/bioc/html/zinbwave.html",
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/methods/zinbwave",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/methods/zinbwave:build_main",
+    "authors": [],
+    "references": {
+      "doi": ["10.1038/s41467-017-02554-5"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "positive",
+    "label": "positive",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "A positive control method.",
+    "description": "A positive control method.",
+    "type": "control_method",
+    "link_code": "https://github.com/openproblems-bio/task_spatial_simulators",
+    "link_documentation": null,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/control_methods/positive",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/control_methods/positive:build_main",
+    "authors": [],
+    "references": {
+      "doi": [],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "negative_shuffle",
+    "label": "negative_shuffle",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "A negative control method which shuffles the input data.",
+    "description": "This control method shuffles the input data as a negative control.",
+    "type": "control_method",
+    "link_code": "https://github.com/openproblems-bio/task_spatial_simulators",
+    "link_documentation": null,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/control_methods/negative_shuffle",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/control_methods/negative_shuffle:build_main",
+    "authors": [],
+    "references": {
+      "doi": [],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "negative_normal",
+    "label": "negative_normal",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "A negative control which generates normal distributed data.",
+    "description": "This control method generates normally distributed data as a negative control,\nusing a fixed mean of 3 and standard deviation of 1.",
+    "type": "control_method",
+    "link_code": "https://github.com/openproblems-bio/task_spatial_simulators",
+    "link_documentation": null,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/control_methods/negative_normal",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/control_methods/negative_normal:build_main",
+    "authors": [],
+    "references": {
+      "doi": [],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  }
+]
diff --git a/spatial_simulators/v0.0.1-rc1/metric_info.json b/spatial_simulators/v0.0.1-rc1/metric_info.json
new file mode 100644
index 0000000..7c09e59
--- /dev/null
+++ b/spatial_simulators/v0.0.1-rc1/metric_info.json
@@ -0,0 +1,704 @@
+[
+  {
+    "name": "clustering_ari",
+    "label": "clustering_ari",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "Adjusted rand index (ARI) measures the similarity between two clusters in real and simulated datasets.",
+    "description": "Adjusted Rand Index used in spatial clustering to measure the similarity between two data clusterings, adjusted for chance.",
+    "maximize": true,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/downstream",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/downstream:build_main",
+    "component_name": "downstream",
+    "authors": [],
+    "references": {
+      "doi": ["10.1145/1553374.1553511"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "clustering_nmi",
+    "label": "clustering_nmi",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "Normalized mutual information (NMI) measures of the mutual dependence between the real and simulated spatial clusters.",
+    "description": "Normalized Mutual Information used in spatial clustering to measure the agreement between two different clusterings, scaled to [0, 1].",
+    "maximize": true,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/downstream",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/downstream:build_main",
+    "component_name": "downstream",
+    "authors": [],
+    "references": {
+      "doi": ["10.1145/1553374.1553511"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "svg_recall",
+    "label": "svg_recall",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "Recall measures the proportion of real SVG correctly identified in the simulated dataset.",
+    "description": "Recall used in identifying spatial variable genes, measuring the true positive rate.",
+    "maximize": true,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/downstream",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/downstream:build_main",
+    "component_name": "downstream",
+    "authors": [],
+    "references": {
+      "doi": ["10.9735/2229-3981"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "svg_precision",
+    "label": "svg_precision",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "Precision measures the proportion of correctly identified items in simulated datasets.",
+    "description": "Precision used in identifying spatial variable genes, measuring the accuracy of positive predictions.",
+    "maximize": true,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/downstream",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/downstream:build_main",
+    "component_name": "downstream",
+    "authors": [],
+    "references": {
+      "doi": ["10.9735/2229-3981"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "ctdeconvolute_rmse",
+    "label": "ctdeconvolute_rmse",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "Root Mean Square deviation is calculated between the true and predicted proportion of per cell type.",
+    "description": "Root Mean Squared Error used in cell type deconvolution to measure the difference between observed and predicted values.",
+    "maximize": false,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/downstream",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/downstream:build_main",
+    "component_name": "downstream",
+    "authors": [],
+    "references": {
+      "doi": ["10.5194/gmd-15-5481-2022"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "ctdeconvolute_jsd",
+    "label": "ctdeconvolute_jsd",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "Jensen-Shannon divergence (JSD) is calculated between the true and predicted proportion per cell type in all spots.",
+    "description": "Jensen-Shannon Divergence used in cell type deconvolution to measure the similarity between two probability distributions.",
+    "maximize": false,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/downstream",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/downstream:build_main",
+    "component_name": "downstream",
+    "authors": [],
+    "references": {
+      "doi": ["10.21105/joss.00765"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "crosscor_mantel",
+    "label": "crosscor_mantel",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "Mantel statistic is the test statistic for the Mantel test, which is a correlation coefficient calculated between bivariate Moran’s I of real dataset and that of in simulation dataset.",
+    "description": "Mantel statistic used in spatial cross-correlation to test the correlation between two distance matrices.",
+    "maximize": true,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/downstream",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/downstream:build_main",
+    "component_name": "downstream",
+    "authors": [],
+    "references": {
+      "doi": ["10.1111/2041-210X.12425"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "crosscor_cosine",
+    "label": "crosscor_cosine",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "Cosine similarity measures similarity between bivariate Moran’s I of real dataset and that of in simulation dataset.",
+    "description": "Cosine similarity used in spatial cross-correlation to measure the cosine of the angle between two non-zero vectors.",
+    "maximize": true,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/downstream",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/downstream:build_main",
+    "component_name": "downstream",
+    "authors": [],
+    "references": {
+      "doi": ["10.1002/asi.20130"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "ks_statistic_frac_zero_genes_zstat",
+    "label": "Fraction of zeros per gene",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "KS statistic of the fraction of zeros per gene.",
+    "description": "The Kolmogorov-Smirnov statistic comparing the fraction of zeros per gene in the real datasets versus the fraction of zeros per gene in the simulated datasets.",
+    "maximize": false,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/ks_statistic_gene_cell",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/ks_statistic_gene_cell:build_main",
+    "component_name": "ks_statistic_gene_cell",
+    "authors": [],
+    "references": {
+      "doi": ["10.1201/9780429485572"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "ks_statistic_frac_zero_cells_zstat",
+    "label": "Fraction of zeros per cell",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "KS statistic of the fraction of zeros per spot (cell).",
+    "description": "The Kolmogorov-Smirnov statistic comparing the fraction of zeros per spot (cell) in the real datasets versus the fraction of zeros per spot (cell) in the simulated datasets.",
+    "maximize": false,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/ks_statistic_gene_cell",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/ks_statistic_gene_cell:build_main",
+    "component_name": "ks_statistic_gene_cell",
+    "authors": [],
+    "references": {
+      "doi": ["10.1201/9780429485572"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "ks_statistic_lib_size_cells_zstat",
+    "label": "Library size",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "KS statistic of the library size.",
+    "description": "The Kolmogorov-Smirnov statistic comparing the total sum of UMI counts across all genes in the real datasets versus the total sum of UMI counts across all genes in the simmulated datasets.",
+    "maximize": false,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/ks_statistic_gene_cell",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/ks_statistic_gene_cell:build_main",
+    "component_name": "ks_statistic_gene_cell",
+    "authors": [],
+    "references": {
+      "doi": ["10.1201/9780429485572"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "ks_statistic_efflib_size_cells_zstat",
+    "label": "Effective library size",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "KS statistic of the effective library size.",
+    "description": "The Kolmogorov-Smirnov statistic comparing the effective library size of the real datasets versus the effective library size of the simulated datasets.",
+    "maximize": false,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/ks_statistic_gene_cell",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/ks_statistic_gene_cell:build_main",
+    "component_name": "ks_statistic_gene_cell",
+    "authors": [],
+    "references": {
+      "doi": ["10.1201/9780429485572"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "ks_statistic_tmm_cells_zstat",
+    "label": "TMM",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "KS statistic of the weight trimmed mean of M-values normalization factor (TMM).",
+    "description": "The Kolmogorov-Smirnov statistic comparing the weight trimmed mean of M-values normalization factor for the real datasets versus the weight trimmed mean of M-values normalization factor for the simulated datasets.",
+    "maximize": false,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/ks_statistic_gene_cell",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/ks_statistic_gene_cell:build_main",
+    "component_name": "ks_statistic_gene_cell",
+    "authors": [],
+    "references": {
+      "doi": ["10.1201/9780429485572"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "ks_statistic_scaled_var_cells_zstat",
+    "label": "Scaled variance cell",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "KS statistic of the spot- (or cell-) level scaled variance of the expression matrix.",
+    "description": "The Kolmogorov-Smirnov statistic comparing the spot-level z-score standardization of the variance of expression matrix in terms of log2(CPM) in the real datasets versus the simulated datasets.",
+    "maximize": false,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/ks_statistic_gene_cell",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/ks_statistic_gene_cell:build_main",
+    "component_name": "ks_statistic_gene_cell",
+    "authors": [],
+    "references": {
+      "doi": ["10.1201/9780429485572"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "ks_statistic_scaled_mean_cells_zstat",
+    "label": "Scaled mean cells",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "KS statistic of the spot- (or cell-) level scaled mean of the expression matrix.",
+    "description": "The Kolmogorov-Smirnov statistic comparing the z-score standardization of the mean of expression matrix in terms of log2(CPM) in the real datasets versus the simulated datasets.",
+    "maximize": false,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/ks_statistic_gene_cell",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/ks_statistic_gene_cell:build_main",
+    "component_name": "ks_statistic_gene_cell",
+    "authors": [],
+    "references": {
+      "doi": ["10.1201/9780429485572"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "ks_statistic_lib_fraczero_cells_zstat",
+    "label": "Library size vs fraction zero",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "KS statistic of the relationship between library size and the proportion of zeros per spot (cell).",
+    "description": "The Kolmogorov-Smirnov statistic comparing the relationship between library size and the proportion of zeros per spot (cell) in the real datasets versus the simulated datasets.",
+    "maximize": false,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/ks_statistic_gene_cell",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/ks_statistic_gene_cell:build_main",
+    "component_name": "ks_statistic_gene_cell",
+    "authors": [],
+    "references": {
+      "doi": ["10.1201/9780429485572"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "ks_statistic_pearson_cells_zstat",
+    "label": "Sample Pearson correlation",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "KS statistic of the sample Pearson correlation.",
+    "description": "The Kolmogorov-Smirnov statistic comparing the sample Pearson correlation of the real datasets versus the sample Pearson correlation of the simulated datasets.",
+    "maximize": false,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/ks_statistic_gene_cell",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/ks_statistic_gene_cell:build_main",
+    "component_name": "ks_statistic_gene_cell",
+    "authors": [],
+    "references": {
+      "doi": ["10.1201/9780429485572"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "ks_statistic_scaled_var_genes_zstat",
+    "label": "Scaled variance genes",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "KS statistic of the gene-level scaled variance of the expression matrix.",
+    "description": "The Kolmogorov-Smirnov statistic comparing the gene-level z-score standardization of the variance of expression matrix in terms of log2(CPM) in the real datasets versus the simulated datasets.",
+    "maximize": false,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/ks_statistic_gene_cell",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/ks_statistic_gene_cell:build_main",
+    "component_name": "ks_statistic_gene_cell",
+    "authors": [],
+    "references": {
+      "doi": ["10.1201/9780429485572"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "ks_statistic_scaled_mean_genes_zstat",
+    "label": "Scaled mean genes",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "KS statistic of the gene-level scaled mean of the expression matrix.",
+    "description": "The Kolmogorov-Smirnov statistic comparing the gene-level z-score standardization of the mean of expression matrix in terms of log2(CPM) in the real datasets versus the simulated datasets.",
+    "maximize": false,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/ks_statistic_gene_cell",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/ks_statistic_gene_cell:build_main",
+    "component_name": "ks_statistic_gene_cell",
+    "authors": [],
+    "references": {
+      "doi": ["10.1201/9780429485572"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "ks_statistic_pearson_genes_zstat",
+    "label": "Gene Pearson correlation",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "KS statistic of the gene Pearson correlation.",
+    "description": "The Kolmogorov-Smirnov statistic comparing the gene Pearson correlation of the real datasets versus the gene Pearson correlation of the simulated datasets.",
+    "maximize": false,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/ks_statistic_gene_cell",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/ks_statistic_gene_cell:build_main",
+    "component_name": "ks_statistic_gene_cell",
+    "authors": [],
+    "references": {
+      "doi": ["10.1201/9780429485572"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "ks_statistic_mean_var_genes_zstat",
+    "label": "Mean vs variance",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "KS statistic of the relationship between mean expression and variance expression.",
+    "description": "The Kolmogorov-Smirnov statistic comparing the relationship between mean expression and variance expression in the real datasets versus the simulated datasets.",
+    "maximize": false,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/ks_statistic_gene_cell",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/ks_statistic_gene_cell:build_main",
+    "component_name": "ks_statistic_gene_cell",
+    "authors": [],
+    "references": {
+      "doi": ["10.1201/9780429485572"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "ks_statistic_mean_fraczero_genes_zstat",
+    "label": "Mean vs fraction zero",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "KS statistic of the relationship between mean expression and the proportion of zero per gene.",
+    "description": "The Kolmogorov-Smirnov statistic comparing the relationship between mean expression and the proportion of zero per gene in the real datasets versus the simulated datasets.",
+    "maximize": false,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/ks_statistic_gene_cell",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/ks_statistic_gene_cell:build_main",
+    "component_name": "ks_statistic_gene_cell",
+    "authors": [],
+    "references": {
+      "doi": ["10.1201/9780429485572"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "ks_statistic_frac_zero_genes_tstat",
+    "label": "Fraction of zeros per gene",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "KS statistic of the fraction of zeros per gene.",
+    "description": "The Kolmogorov-Smirnov statistic comparing the fraction of zeros per gene in the real datasets versus the fraction of zeros per gene in the simulated datasets.",
+    "maximize": false,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/ks_statistic_gene_cell",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/ks_statistic_gene_cell:build_main",
+    "component_name": "ks_statistic_gene_cell",
+    "authors": [],
+    "references": {
+      "doi": ["10.1201/9780429485572"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "ks_statistic_frac_zero_cells_tstat",
+    "label": "Fraction of zeros per cell",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "KS statistic of the fraction of zeros per spot (cell).",
+    "description": "The Kolmogorov-Smirnov statistic comparing the fraction of zeros per spot (cell) in the real datasets versus the fraction of zeros per spot (cell) in the simulated datasets.",
+    "maximize": false,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/ks_statistic_gene_cell",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/ks_statistic_gene_cell:build_main",
+    "component_name": "ks_statistic_gene_cell",
+    "authors": [],
+    "references": {
+      "doi": ["10.1201/9780429485572"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "ks_statistic_lib_size_cells_tstat",
+    "label": "Library size",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "KS statistic of the library size.",
+    "description": "The Kolmogorov-Smirnov statistic comparing the total sum of UMI counts across all genes in the real datasets versus the total sum of UMI counts across all genes in the simmulated datasets.",
+    "maximize": false,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/ks_statistic_gene_cell",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/ks_statistic_gene_cell:build_main",
+    "component_name": "ks_statistic_gene_cell",
+    "authors": [],
+    "references": {
+      "doi": ["10.1201/9780429485572"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "ks_statistic_efflib_size_cells_tstat",
+    "label": "Effective library size",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "KS statistic of the effective library size.",
+    "description": "The Kolmogorov-Smirnov statistic comparing the effective library size of the real datasets versus the effective library size of the simulated datasets.",
+    "maximize": false,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/ks_statistic_gene_cell",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/ks_statistic_gene_cell:build_main",
+    "component_name": "ks_statistic_gene_cell",
+    "authors": [],
+    "references": {
+      "doi": ["10.1201/9780429485572"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "ks_statistic_tmm_cells_tstat",
+    "label": "TMM",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "KS statistic of the weight trimmed mean of M-values normalization factor (TMM).",
+    "description": "The Kolmogorov-Smirnov statistic comparing the weight trimmed mean of M-values normalization factor for the real datasets versus the weight trimmed mean of M-values normalization factor for the simulated datasets.",
+    "maximize": false,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/ks_statistic_gene_cell",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/ks_statistic_gene_cell:build_main",
+    "component_name": "ks_statistic_gene_cell",
+    "authors": [],
+    "references": {
+      "doi": ["10.1201/9780429485572"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "ks_statistic_scaled_var_cells_tstat",
+    "label": "Scaled variance cell",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "KS statistic of the spot- (or cell-) level scaled variance of the expression matrix.",
+    "description": "The Kolmogorov-Smirnov statistic comparing the spot-level z-score standardization of the variance of expression matrix in terms of log2(CPM) in the real datasets versus the simulated datasets.",
+    "maximize": false,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/ks_statistic_gene_cell",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/ks_statistic_gene_cell:build_main",
+    "component_name": "ks_statistic_gene_cell",
+    "authors": [],
+    "references": {
+      "doi": ["10.1201/9780429485572"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "ks_statistic_scaled_mean_cells_tstat",
+    "label": "Scaled mean cells",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "KS statistic of the spot- (or cell-) level scaled mean of the expression matrix.",
+    "description": "The Kolmogorov-Smirnov statistic comparing the z-score standardization of the mean of expression matrix in terms of log2(CPM) in the real datasets versus the simulated datasets.",
+    "maximize": false,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/ks_statistic_gene_cell",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/ks_statistic_gene_cell:build_main",
+    "component_name": "ks_statistic_gene_cell",
+    "authors": [],
+    "references": {
+      "doi": ["10.1201/9780429485572"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "ks_statistic_lib_fraczero_cells_tstat",
+    "label": "Library size vs fraction zero",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "KS statistic of the relationship between library size and the proportion of zeros per spot (cell).",
+    "description": "The Kolmogorov-Smirnov statistic comparing the relationship between library size and the proportion of zeros per spot (cell) in the real datasets versus the simulated datasets.",
+    "maximize": false,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/ks_statistic_gene_cell",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/ks_statistic_gene_cell:build_main",
+    "component_name": "ks_statistic_gene_cell",
+    "authors": [],
+    "references": {
+      "doi": ["10.1201/9780429485572"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "ks_statistic_pearson_cells_tstat",
+    "label": "Sample Pearson correlation",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "KS statistic of the sample Pearson correlation.",
+    "description": "The Kolmogorov-Smirnov statistic comparing the sample Pearson correlation of the real datasets versus the sample Pearson correlation of the simulated datasets.",
+    "maximize": false,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/ks_statistic_gene_cell",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/ks_statistic_gene_cell:build_main",
+    "component_name": "ks_statistic_gene_cell",
+    "authors": [],
+    "references": {
+      "doi": ["10.1201/9780429485572"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "ks_statistic_scaled_var_genes_tstat",
+    "label": "Scaled variance genes",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "KS statistic of the gene-level scaled variance of the expression matrix.",
+    "description": "The Kolmogorov-Smirnov statistic comparing the gene-level z-score standardization of the variance of expression matrix in terms of log2(CPM) in the real datasets versus the simulated datasets.",
+    "maximize": false,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/ks_statistic_gene_cell",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/ks_statistic_gene_cell:build_main",
+    "component_name": "ks_statistic_gene_cell",
+    "authors": [],
+    "references": {
+      "doi": ["10.1201/9780429485572"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "ks_statistic_scaled_mean_genes_tstat",
+    "label": "Scaled mean genes",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "KS statistic of the gene-level scaled mean of the expression matrix.",
+    "description": "The Kolmogorov-Smirnov statistic comparing the gene-level z-score standardization of the mean of expression matrix in terms of log2(CPM) in the real datasets versus the simulated datasets.",
+    "maximize": false,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/ks_statistic_gene_cell",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/ks_statistic_gene_cell:build_main",
+    "component_name": "ks_statistic_gene_cell",
+    "authors": [],
+    "references": {
+      "doi": ["10.1201/9780429485572"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "ks_statistic_pearson_genes_tstat",
+    "label": "Gene Pearson correlation",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "KS statistic of the gene Pearson correlation.",
+    "description": "The Kolmogorov-Smirnov statistic comparing the gene Pearson correlation of the real datasets versus the gene Pearson correlation of the simulated datasets.",
+    "maximize": false,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/ks_statistic_gene_cell",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/ks_statistic_gene_cell:build_main",
+    "component_name": "ks_statistic_gene_cell",
+    "authors": [],
+    "references": {
+      "doi": ["10.1201/9780429485572"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "ks_statistic_mean_var_genes_tstat",
+    "label": "Mean vs variance",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "KS statistic of the relationship between mean expression and variance expression.",
+    "description": "The Kolmogorov-Smirnov statistic comparing the relationship between mean expression and variance expression in the real datasets versus the simulated datasets.",
+    "maximize": false,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/ks_statistic_gene_cell",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/ks_statistic_gene_cell:build_main",
+    "component_name": "ks_statistic_gene_cell",
+    "authors": [],
+    "references": {
+      "doi": ["10.1201/9780429485572"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "ks_statistic_mean_fraczero_genes_tstat",
+    "label": "Mean vs fraction zero",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "KS statistic of the relationship between mean expression and the proportion of zero per gene.",
+    "description": "The Kolmogorov-Smirnov statistic comparing the relationship between mean expression and the proportion of zero per gene in the real datasets versus the simulated datasets.",
+    "maximize": false,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/ks_statistic_gene_cell",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/ks_statistic_gene_cell:build_main",
+    "component_name": "ks_statistic_gene_cell",
+    "authors": [],
+    "references": {
+      "doi": ["10.1201/9780429485572"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "ks_statistic_L_stats",
+    "label": "L statistics",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "KS statistic of the L statistics",
+    "description": "The Kolmogorov-Smirnov statistic comparing the L statistics in the real datasets versus the L statistics in the simulated datasets.",
+    "maximize": false,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/ks_statistic_sc_features",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/ks_statistic_sc_features:build_main",
+    "component_name": "ks_statistic_sc_features",
+    "authors": [],
+    "references": {
+      "doi": ["10.1201/9780429485572"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "ks_statistic_nn_correlation",
+    "label": "Nearest-neighbour correlation",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "KS statistic of the nearest-neighbour correlation.",
+    "description": "The Kolmogorov-Smirnov statistic comparing the nn correlation in the real datasets versus the nn correlation in the simulated datasets.",
+    "maximize": false,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/ks_statistic_sc_features",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/ks_statistic_sc_features:build_main",
+    "component_name": "ks_statistic_sc_features",
+    "authors": [],
+    "references": {
+      "doi": ["10.1201/9780429485572"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  },
+  {
+    "name": "ks_statistic_morans_I",
+    "label": "Moran's I",
+    "commit": "c0ca0170b86a047ba4e64ef0b667eee6e1b83772",
+    "summary": "KS statistic of Moran's I.",
+    "description": "The Kolmogorov-Smirnov statistic comparing the Moran's I of the real datasets versus the Moran's I of the simulated datasets.",
+    "maximize": false,
+    "link_implementation": "https://github.com/openproblems-bio/task_spatial_simulators/blob/c0ca0170b86a047ba4e64ef0b667eee6e1b83772/src/metrics/ks_statistic_sc_features",
+    "link_container_image": "https://ghcr.io/openproblems-bio/task_spatial_simulators/metrics/ks_statistic_sc_features:build_main",
+    "component_name": "ks_statistic_sc_features",
+    "authors": [],
+    "references": {
+      "doi": ["10.1201/9780429485572"],
+      "bibtex": []
+    },
+    "additional_info": {},
+    "version": "build_main"
+  }
+]
diff --git a/spatial_simulators/v0.0.1-rc1/quality_control.json b/spatial_simulators/v0.0.1-rc1/quality_control.json
new file mode 100644
index 0000000..c23a7aa
--- /dev/null
+++ b/spatial_simulators/v0.0.1-rc1/quality_control.json
@@ -0,0 +1,3665 @@
+[
+  {
+    "category": "Task info",
+    "label": "Info field 'name' % missing",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_missing <= 0",
+    "message": "Task info field 'name' should be defined\n  Task: spatial_simulators\n  Field: name\n  Percentage missing: 0"
+  },
+  {
+    "category": "Task info",
+    "label": "Info field 'label' % missing",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_missing <= 0",
+    "message": "Task info field 'label' should be defined\n  Task: spatial_simulators\n  Field: label\n  Percentage missing: 0"
+  },
+  {
+    "category": "Task info",
+    "label": "Info field 'summary' % missing",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_missing <= 0",
+    "message": "Task info field 'summary' should be defined\n  Task: spatial_simulators\n  Field: summary\n  Percentage missing: 0"
+  },
+  {
+    "category": "Task info",
+    "label": "Info field 'description' % missing",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_missing <= 0",
+    "message": "Task info field 'description' should be defined\n  Task: spatial_simulators\n  Field: description\n  Percentage missing: 0"
+  },
+  {
+    "category": "Dataset info",
+    "label": "Info field 'name' % missing",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_missing <= 0",
+    "message": "Dataset info field 'name' should be defined\n  Task: spatial_simulators\n  Field: name\n  Percentage missing: 0"
+  },
+  {
+    "category": "Dataset info",
+    "label": "Info field 'label' % missing",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_missing <= 0",
+    "message": "Dataset info field 'label' should be defined\n  Task: spatial_simulators\n  Field: label\n  Percentage missing: 0"
+  },
+  {
+    "category": "Dataset info",
+    "label": "Info field 'summary' % missing",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_missing <= 0",
+    "message": "Dataset info field 'summary' should be defined\n  Task: spatial_simulators\n  Field: summary\n  Percentage missing: 0"
+  },
+  {
+    "category": "Dataset info",
+    "label": "Info field 'description' % missing",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_missing <= 0",
+    "message": "Dataset info field 'description' should be defined\n  Task: spatial_simulators\n  Field: description\n  Percentage missing: 0"
+  },
+  {
+    "category": "Dataset info",
+    "label": "Info field 'references' % missing",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_missing <= 0",
+    "message": "Dataset info field 'references' should be defined\n  Task: spatial_simulators\n  Field: references\n  Percentage missing: 0"
+  },
+  {
+    "category": "Method info",
+    "label": "Info field 'name' % missing",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_missing <= 0",
+    "message": "Method info field 'name' should be defined\n  Task: spatial_simulators\n  Field: name\n  Percentage missing: 0"
+  },
+  {
+    "category": "Method info",
+    "label": "Info field 'label' % missing",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_missing <= 0",
+    "message": "Method info field 'label' should be defined\n  Task: spatial_simulators\n  Field: label\n  Percentage missing: 0"
+  },
+  {
+    "category": "Method info",
+    "label": "Info field 'commit' % missing",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_missing <= 0",
+    "message": "Method info field 'commit' should be defined\n  Task: spatial_simulators\n  Field: commit\n  Percentage missing: 0"
+  },
+  {
+    "category": "Method info",
+    "label": "Info field 'summary' % missing",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_missing <= 0",
+    "message": "Method info field 'summary' should be defined\n  Task: spatial_simulators\n  Field: summary\n  Percentage missing: 0"
+  },
+  {
+    "category": "Method info",
+    "label": "Info field 'description' % missing",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_missing <= 0",
+    "message": "Method info field 'description' should be defined\n  Task: spatial_simulators\n  Field: description\n  Percentage missing: 0"
+  },
+  {
+    "category": "Method info",
+    "label": "Info field 'references' % missing",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_missing <= 0",
+    "message": "Method info field 'references' should be defined\n  Task: spatial_simulators\n  Field: references\n  Percentage missing: 0"
+  },
+  {
+    "category": "Metric info",
+    "label": "Info field 'name' % missing",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_missing <= 0",
+    "message": "Metric info field 'name' should be defined\n  Task: spatial_simulators\n  Field: name\n  Percentage missing: 0"
+  },
+  {
+    "category": "Metric info",
+    "label": "Info field 'label' % missing",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_missing <= 0",
+    "message": "Metric info field 'label' should be defined\n  Task: spatial_simulators\n  Field: label\n  Percentage missing: 0"
+  },
+  {
+    "category": "Metric info",
+    "label": "Info field 'commit' % missing",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_missing <= 0",
+    "message": "Metric info field 'commit' should be defined\n  Task: spatial_simulators\n  Field: commit\n  Percentage missing: 0"
+  },
+  {
+    "category": "Metric info",
+    "label": "Info field 'summary' % missing",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_missing <= 0",
+    "message": "Metric info field 'summary' should be defined\n  Task: spatial_simulators\n  Field: summary\n  Percentage missing: 0"
+  },
+  {
+    "category": "Metric info",
+    "label": "Info field 'description' % missing",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_missing <= 0",
+    "message": "Metric info field 'description' should be defined\n  Task: spatial_simulators\n  Field: description\n  Percentage missing: 0"
+  },
+  {
+    "category": "Metric info",
+    "label": "Info field 'references' % missing",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_missing <= 0",
+    "message": "Metric info field 'references' should be defined\n  Task: spatial_simulators\n  Field: references\n  Percentage missing: 0"
+  },
+  {
+    "category": "Raw results",
+    "label": "Task number of results",
+    "value": 1004,
+    "severity": 3,
+    "severity_value": 7.6597,
+    "condition": "length(dataset_info) * length(results) == length(method_info) * length(metric_info)",
+    "message": "Number of results should be equal to #datasets × #methods × #metrics \n  Task: spatial_simulators\n  Number of results: 1004\n  Number of datasets: 10\n  Number of methods: 11\n  Number of metrics: 39\n  Expected number of results: 4290\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Dataset 'osteosarcoma' % missing",
+    "value": 0.7529,
+    "severity": 3,
+    "severity_value": 7.5291,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Dataset: osteosarcoma\n  Number of results: 106\n  Expected number of results: 429\n  Percentage missing: 75%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Dataset 'cortex' % missing",
+    "value": 0.7506,
+    "severity": 3,
+    "severity_value": 7.5058,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Dataset: cortex\n  Number of results: 107\n  Expected number of results: 429\n  Percentage missing: 75%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Dataset 'breast' % missing",
+    "value": 0.7879,
+    "severity": 3,
+    "severity_value": 7.8788,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Dataset: breast\n  Number of results: 91\n  Expected number of results: 429\n  Percentage missing: 79%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Dataset 'prostate' % missing",
+    "value": 0.7646,
+    "severity": 3,
+    "severity_value": 7.6457,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Dataset: prostate\n  Number of results: 101\n  Expected number of results: 429\n  Percentage missing: 76%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Dataset 'gastrulation' % missing",
+    "value": 0.7483,
+    "severity": 3,
+    "severity_value": 7.4825,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Dataset: gastrulation\n  Number of results: 108\n  Expected number of results: 429\n  Percentage missing: 75%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Dataset 'brain' % missing",
+    "value": 0.7925,
+    "severity": 3,
+    "severity_value": 7.9254,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Dataset: brain\n  Number of results: 89\n  Expected number of results: 429\n  Percentage missing: 79%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Dataset 'pdac' % missing",
+    "value": 0.7599,
+    "severity": 3,
+    "severity_value": 7.5991,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Dataset: pdac\n  Number of results: 103\n  Expected number of results: 429\n  Percentage missing: 76%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Dataset 'olfactorybulb' % missing",
+    "value": 0.7483,
+    "severity": 3,
+    "severity_value": 7.4825,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Dataset: olfactorybulb\n  Number of results: 108\n  Expected number of results: 429\n  Percentage missing: 75%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Dataset 'fibrosarcoma' % missing",
+    "value": 0.7552,
+    "severity": 3,
+    "severity_value": 7.5524,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Dataset: fibrosarcoma\n  Number of results: 105\n  Expected number of results: 429\n  Percentage missing: 76%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Dataset 'hindlimbmuscle' % missing",
+    "value": 0.7995,
+    "severity": 3,
+    "severity_value": 7.9953,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Dataset: hindlimbmuscle\n  Number of results: 86\n  Expected number of results: 429\n  Percentage missing: 80%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Method 'scdesign2' % missing",
+    "value": 0.7436,
+    "severity": 3,
+    "severity_value": 7.4359,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Method: scdesign2\n  Number of results: 100\n  Expected number of results: 390\n  Percentage missing: 74%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Method 'scdesign3_nb' % missing",
+    "value": 0.7385,
+    "severity": 3,
+    "severity_value": 7.3846,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Method: scdesign3_nb\n  Number of results: 102\n  Expected number of results: 390\n  Percentage missing: 74%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Method 'scdesign3_poisson' % missing",
+    "value": 0.7564,
+    "severity": 3,
+    "severity_value": 7.5641,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Method: scdesign3_poisson\n  Number of results: 95\n  Expected number of results: 390\n  Percentage missing: 76%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Method 'sparsim' % missing",
+    "value": 0.7436,
+    "severity": 3,
+    "severity_value": 7.4359,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Method: sparsim\n  Number of results: 100\n  Expected number of results: 390\n  Percentage missing: 74%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Method 'splatter' % missing",
+    "value": 0.7333,
+    "severity": 3,
+    "severity_value": 7.3333,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Method: splatter\n  Number of results: 104\n  Expected number of results: 390\n  Percentage missing: 73%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Method 'srtsim' % missing",
+    "value": 0.7436,
+    "severity": 3,
+    "severity_value": 7.4359,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Method: srtsim\n  Number of results: 100\n  Expected number of results: 390\n  Percentage missing: 74%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Method 'symsim' % missing",
+    "value": 0.7436,
+    "severity": 3,
+    "severity_value": 7.4359,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Method: symsim\n  Number of results: 100\n  Expected number of results: 390\n  Percentage missing: 74%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Method 'zinbwave' % missing",
+    "value": 1,
+    "severity": 3,
+    "severity_value": 10,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Method: zinbwave\n  Number of results: 0\n  Expected number of results: 390\n  Percentage missing: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Method 'positive' % missing",
+    "value": 0.7282,
+    "severity": 3,
+    "severity_value": 7.2821,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Method: positive\n  Number of results: 106\n  Expected number of results: 390\n  Percentage missing: 73%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Method 'negative_shuffle' % missing",
+    "value": 0.7462,
+    "severity": 3,
+    "severity_value": 7.4615,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Method: negative_shuffle\n  Number of results: 99\n  Expected number of results: 390\n  Percentage missing: 75%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Method 'negative_normal' % missing",
+    "value": 0.7487,
+    "severity": 3,
+    "severity_value": 7.4872,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Method: negative_normal\n  Number of results: 98\n  Expected number of results: 390\n  Percentage missing: 75%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'clustering_ari' % missing",
+    "value": 0.1,
+    "severity": 0,
+    "severity_value": 1,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: clustering_ari\n  Number of results: 99\n  Expected number of results: 110\n  Percentage missing: 10%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'clustering_nmi' % missing",
+    "value": 0.1,
+    "severity": 0,
+    "severity_value": 1,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: clustering_nmi\n  Number of results: 99\n  Expected number of results: 110\n  Percentage missing: 10%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'svg_recall' % missing",
+    "value": 0.2818,
+    "severity": 2,
+    "severity_value": 2.8182,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: svg_recall\n  Number of results: 79\n  Expected number of results: 110\n  Percentage missing: 28%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'svg_precision' % missing",
+    "value": 0.4091,
+    "severity": 3,
+    "severity_value": 4.0909,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: svg_precision\n  Number of results: 65\n  Expected number of results: 110\n  Percentage missing: 41%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ctdeconvolute_rmse' % missing",
+    "value": 0.1,
+    "severity": 0,
+    "severity_value": 1,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: ctdeconvolute_rmse\n  Number of results: 99\n  Expected number of results: 110\n  Percentage missing: 10%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ctdeconvolute_jsd' % missing",
+    "value": 0.1,
+    "severity": 0,
+    "severity_value": 1,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: ctdeconvolute_jsd\n  Number of results: 99\n  Expected number of results: 110\n  Percentage missing: 10%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'crosscor_mantel' % missing",
+    "value": 0.1,
+    "severity": 0,
+    "severity_value": 1,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: crosscor_mantel\n  Number of results: 99\n  Expected number of results: 110\n  Percentage missing: 10%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'crosscor_cosine' % missing",
+    "value": 0.3818,
+    "severity": 3,
+    "severity_value": 3.8182,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: crosscor_cosine\n  Number of results: 68\n  Expected number of results: 110\n  Percentage missing: 38%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_frac_zero_genes_zstat' % missing",
+    "value": 1,
+    "severity": 3,
+    "severity_value": 10,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: ks_statistic_frac_zero_genes_zstat\n  Number of results: 0\n  Expected number of results: 110\n  Percentage missing: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_frac_zero_cells_zstat' % missing",
+    "value": 1,
+    "severity": 3,
+    "severity_value": 10,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: ks_statistic_frac_zero_cells_zstat\n  Number of results: 0\n  Expected number of results: 110\n  Percentage missing: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_lib_size_cells_zstat' % missing",
+    "value": 1,
+    "severity": 3,
+    "severity_value": 10,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: ks_statistic_lib_size_cells_zstat\n  Number of results: 0\n  Expected number of results: 110\n  Percentage missing: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_efflib_size_cells_zstat' % missing",
+    "value": 1,
+    "severity": 3,
+    "severity_value": 10,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: ks_statistic_efflib_size_cells_zstat\n  Number of results: 0\n  Expected number of results: 110\n  Percentage missing: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_tmm_cells_zstat' % missing",
+    "value": 1,
+    "severity": 3,
+    "severity_value": 10,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: ks_statistic_tmm_cells_zstat\n  Number of results: 0\n  Expected number of results: 110\n  Percentage missing: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_scaled_var_cells_zstat' % missing",
+    "value": 1,
+    "severity": 3,
+    "severity_value": 10,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: ks_statistic_scaled_var_cells_zstat\n  Number of results: 0\n  Expected number of results: 110\n  Percentage missing: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_scaled_mean_cells_zstat' % missing",
+    "value": 1,
+    "severity": 3,
+    "severity_value": 10,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: ks_statistic_scaled_mean_cells_zstat\n  Number of results: 0\n  Expected number of results: 110\n  Percentage missing: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_lib_fraczero_cells_zstat' % missing",
+    "value": 1,
+    "severity": 3,
+    "severity_value": 10,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: ks_statistic_lib_fraczero_cells_zstat\n  Number of results: 0\n  Expected number of results: 110\n  Percentage missing: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_pearson_cells_zstat' % missing",
+    "value": 1,
+    "severity": 3,
+    "severity_value": 10,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: ks_statistic_pearson_cells_zstat\n  Number of results: 0\n  Expected number of results: 110\n  Percentage missing: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_scaled_var_genes_zstat' % missing",
+    "value": 1,
+    "severity": 3,
+    "severity_value": 10,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: ks_statistic_scaled_var_genes_zstat\n  Number of results: 0\n  Expected number of results: 110\n  Percentage missing: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_scaled_mean_genes_zstat' % missing",
+    "value": 1,
+    "severity": 3,
+    "severity_value": 10,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: ks_statistic_scaled_mean_genes_zstat\n  Number of results: 0\n  Expected number of results: 110\n  Percentage missing: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_pearson_genes_zstat' % missing",
+    "value": 1,
+    "severity": 3,
+    "severity_value": 10,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: ks_statistic_pearson_genes_zstat\n  Number of results: 0\n  Expected number of results: 110\n  Percentage missing: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_mean_var_genes_zstat' % missing",
+    "value": 1,
+    "severity": 3,
+    "severity_value": 10,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: ks_statistic_mean_var_genes_zstat\n  Number of results: 0\n  Expected number of results: 110\n  Percentage missing: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_mean_fraczero_genes_zstat' % missing",
+    "value": 1,
+    "severity": 3,
+    "severity_value": 10,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: ks_statistic_mean_fraczero_genes_zstat\n  Number of results: 0\n  Expected number of results: 110\n  Percentage missing: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_frac_zero_genes_tstat' % missing",
+    "value": 1,
+    "severity": 3,
+    "severity_value": 10,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: ks_statistic_frac_zero_genes_tstat\n  Number of results: 0\n  Expected number of results: 110\n  Percentage missing: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_frac_zero_cells_tstat' % missing",
+    "value": 1,
+    "severity": 3,
+    "severity_value": 10,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: ks_statistic_frac_zero_cells_tstat\n  Number of results: 0\n  Expected number of results: 110\n  Percentage missing: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_lib_size_cells_tstat' % missing",
+    "value": 1,
+    "severity": 3,
+    "severity_value": 10,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: ks_statistic_lib_size_cells_tstat\n  Number of results: 0\n  Expected number of results: 110\n  Percentage missing: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_efflib_size_cells_tstat' % missing",
+    "value": 1,
+    "severity": 3,
+    "severity_value": 10,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: ks_statistic_efflib_size_cells_tstat\n  Number of results: 0\n  Expected number of results: 110\n  Percentage missing: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_tmm_cells_tstat' % missing",
+    "value": 1,
+    "severity": 3,
+    "severity_value": 10,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: ks_statistic_tmm_cells_tstat\n  Number of results: 0\n  Expected number of results: 110\n  Percentage missing: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_scaled_var_cells_tstat' % missing",
+    "value": 1,
+    "severity": 3,
+    "severity_value": 10,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: ks_statistic_scaled_var_cells_tstat\n  Number of results: 0\n  Expected number of results: 110\n  Percentage missing: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_scaled_mean_cells_tstat' % missing",
+    "value": 1,
+    "severity": 3,
+    "severity_value": 10,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: ks_statistic_scaled_mean_cells_tstat\n  Number of results: 0\n  Expected number of results: 110\n  Percentage missing: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_lib_fraczero_cells_tstat' % missing",
+    "value": 1,
+    "severity": 3,
+    "severity_value": 10,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: ks_statistic_lib_fraczero_cells_tstat\n  Number of results: 0\n  Expected number of results: 110\n  Percentage missing: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_pearson_cells_tstat' % missing",
+    "value": 1,
+    "severity": 3,
+    "severity_value": 10,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: ks_statistic_pearson_cells_tstat\n  Number of results: 0\n  Expected number of results: 110\n  Percentage missing: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_scaled_var_genes_tstat' % missing",
+    "value": 1,
+    "severity": 3,
+    "severity_value": 10,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: ks_statistic_scaled_var_genes_tstat\n  Number of results: 0\n  Expected number of results: 110\n  Percentage missing: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_scaled_mean_genes_tstat' % missing",
+    "value": 1,
+    "severity": 3,
+    "severity_value": 10,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: ks_statistic_scaled_mean_genes_tstat\n  Number of results: 0\n  Expected number of results: 110\n  Percentage missing: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_pearson_genes_tstat' % missing",
+    "value": 1,
+    "severity": 3,
+    "severity_value": 10,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: ks_statistic_pearson_genes_tstat\n  Number of results: 0\n  Expected number of results: 110\n  Percentage missing: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_mean_var_genes_tstat' % missing",
+    "value": 1,
+    "severity": 3,
+    "severity_value": 10,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: ks_statistic_mean_var_genes_tstat\n  Number of results: 0\n  Expected number of results: 110\n  Percentage missing: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_mean_fraczero_genes_tstat' % missing",
+    "value": 1,
+    "severity": 3,
+    "severity_value": 10,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: ks_statistic_mean_fraczero_genes_tstat\n  Number of results: 0\n  Expected number of results: 110\n  Percentage missing: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_L_stats' % missing",
+    "value": 0.1,
+    "severity": 0,
+    "severity_value": 1,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: ks_statistic_L_stats\n  Number of results: 99\n  Expected number of results: 110\n  Percentage missing: 10%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_nn_correlation' % missing",
+    "value": 0.1,
+    "severity": 0,
+    "severity_value": 1,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: ks_statistic_nn_correlation\n  Number of results: 99\n  Expected number of results: 110\n  Percentage missing: 10%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_morans_I' % missing",
+    "value": 0.1,
+    "severity": 0,
+    "severity_value": 1,
+    "condition": "pct_missing <= 0.1",
+    "message": "Percentage of missing results should be less than 10%\n  Task: spatial_simulators\n  Metric: ks_statistic_morans_I\n  Number of results: 99\n  Expected number of results: 110\n  Percentage missing: 10%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Task number of successful processes",
+    "value": 396,
+    "severity": 0,
+    "severity_value": 0.2703,
+    "condition": "sum(results$succeeded) + sum(metric_component_results$succeeded) == nrow(results) + nrow(metric_component_results)",
+    "message": "Number of successful processes should be equal to the number of attempted processes\n  Task: spatial_simulators\n  Succeeded processes: 396\n  Attempted processes: 407\n  Percentage failed: 3%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Dataset 'osteosarcoma' % failed",
+    "value": 0.0909,
+    "severity": 0,
+    "severity_value": 0.9091,
+    "condition": "pct_failed <= 0.1",
+    "message": "Percentage of failed processes should be less than 10%\n  Task: spatial_simulators\n  Dataset: osteosarcoma\n  Succeeded processes: 10\n  Attempted processes: 11\n  Percentage failed: 9%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Dataset 'cortex' % failed",
+    "value": 0.0909,
+    "severity": 0,
+    "severity_value": 0.9091,
+    "condition": "pct_failed <= 0.1",
+    "message": "Percentage of failed processes should be less than 10%\n  Task: spatial_simulators\n  Dataset: cortex\n  Succeeded processes: 10\n  Attempted processes: 11\n  Percentage failed: 9%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Dataset 'breast' % failed",
+    "value": 0.1818,
+    "severity": 1,
+    "severity_value": 1.8182,
+    "condition": "pct_failed <= 0.1",
+    "message": "Percentage of failed processes should be less than 10%\n  Task: spatial_simulators\n  Dataset: breast\n  Succeeded processes: 9\n  Attempted processes: 11\n  Percentage failed: 18%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Dataset 'prostate' % failed",
+    "value": 0.0909,
+    "severity": 0,
+    "severity_value": 0.9091,
+    "condition": "pct_failed <= 0.1",
+    "message": "Percentage of failed processes should be less than 10%\n  Task: spatial_simulators\n  Dataset: prostate\n  Succeeded processes: 10\n  Attempted processes: 11\n  Percentage failed: 9%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Dataset 'gastrulation' % failed",
+    "value": 0.0909,
+    "severity": 0,
+    "severity_value": 0.9091,
+    "condition": "pct_failed <= 0.1",
+    "message": "Percentage of failed processes should be less than 10%\n  Task: spatial_simulators\n  Dataset: gastrulation\n  Succeeded processes: 10\n  Attempted processes: 11\n  Percentage failed: 9%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Dataset 'brain' % failed",
+    "value": 0.0909,
+    "severity": 0,
+    "severity_value": 0.9091,
+    "condition": "pct_failed <= 0.1",
+    "message": "Percentage of failed processes should be less than 10%\n  Task: spatial_simulators\n  Dataset: brain\n  Succeeded processes: 10\n  Attempted processes: 11\n  Percentage failed: 9%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Dataset 'pdac' % failed",
+    "value": 0.0909,
+    "severity": 0,
+    "severity_value": 0.9091,
+    "condition": "pct_failed <= 0.1",
+    "message": "Percentage of failed processes should be less than 10%\n  Task: spatial_simulators\n  Dataset: pdac\n  Succeeded processes: 10\n  Attempted processes: 11\n  Percentage failed: 9%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Dataset 'olfactorybulb' % failed",
+    "value": 0.0909,
+    "severity": 0,
+    "severity_value": 0.9091,
+    "condition": "pct_failed <= 0.1",
+    "message": "Percentage of failed processes should be less than 10%\n  Task: spatial_simulators\n  Dataset: olfactorybulb\n  Succeeded processes: 10\n  Attempted processes: 11\n  Percentage failed: 9%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Dataset 'fibrosarcoma' % failed",
+    "value": 0.0909,
+    "severity": 0,
+    "severity_value": 0.9091,
+    "condition": "pct_failed <= 0.1",
+    "message": "Percentage of failed processes should be less than 10%\n  Task: spatial_simulators\n  Dataset: fibrosarcoma\n  Succeeded processes: 10\n  Attempted processes: 11\n  Percentage failed: 9%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Dataset 'hindlimbmuscle' % failed",
+    "value": 0.0909,
+    "severity": 0,
+    "severity_value": 0.9091,
+    "condition": "pct_failed <= 0.1",
+    "message": "Percentage of failed processes should be less than 10%\n  Task: spatial_simulators\n  Dataset: hindlimbmuscle\n  Succeeded processes: 10\n  Attempted processes: 11\n  Percentage failed: 9%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Method 'scdesign2' % failed",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_failed <= 0.1",
+    "message": "Percentage of failed processes should be less than 10%\n  Task: spatial_simulators\n  Method: scdesign2\n  Succeeded processes: 10\n  Attempted processes: 10\n  Percentage failed: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Method 'scdesign3_nb' % failed",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_failed <= 0.1",
+    "message": "Percentage of failed processes should be less than 10%\n  Task: spatial_simulators\n  Method: scdesign3_nb\n  Succeeded processes: 10\n  Attempted processes: 10\n  Percentage failed: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Method 'scdesign3_poisson' % failed",
+    "value": 0.1,
+    "severity": 0,
+    "severity_value": 1,
+    "condition": "pct_failed <= 0.1",
+    "message": "Percentage of failed processes should be less than 10%\n  Task: spatial_simulators\n  Method: scdesign3_poisson\n  Succeeded processes: 9\n  Attempted processes: 10\n  Percentage failed: 10%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Method 'sparsim' % failed",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_failed <= 0.1",
+    "message": "Percentage of failed processes should be less than 10%\n  Task: spatial_simulators\n  Method: sparsim\n  Succeeded processes: 10\n  Attempted processes: 10\n  Percentage failed: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Method 'splatter' % failed",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_failed <= 0.1",
+    "message": "Percentage of failed processes should be less than 10%\n  Task: spatial_simulators\n  Method: splatter\n  Succeeded processes: 10\n  Attempted processes: 10\n  Percentage failed: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Method 'srtsim' % failed",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_failed <= 0.1",
+    "message": "Percentage of failed processes should be less than 10%\n  Task: spatial_simulators\n  Method: srtsim\n  Succeeded processes: 10\n  Attempted processes: 10\n  Percentage failed: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Method 'symsim' % failed",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_failed <= 0.1",
+    "message": "Percentage of failed processes should be less than 10%\n  Task: spatial_simulators\n  Method: symsim\n  Succeeded processes: 10\n  Attempted processes: 10\n  Percentage failed: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Method 'zinbwave' % failed",
+    "value": 1,
+    "severity": 3,
+    "severity_value": 10,
+    "condition": "pct_failed <= 0.1",
+    "message": "Percentage of failed processes should be less than 10%\n  Task: spatial_simulators\n  Method: zinbwave\n  Succeeded processes: 0\n  Attempted processes: 10\n  Percentage failed: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Method 'positive' % failed",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_failed <= 0.1",
+    "message": "Percentage of failed processes should be less than 10%\n  Task: spatial_simulators\n  Method: positive\n  Succeeded processes: 10\n  Attempted processes: 10\n  Percentage failed: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Method 'negative_shuffle' % failed",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_failed <= 0.1",
+    "message": "Percentage of failed processes should be less than 10%\n  Task: spatial_simulators\n  Method: negative_shuffle\n  Succeeded processes: 10\n  Attempted processes: 10\n  Percentage failed: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Method 'negative_normal' % failed",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_failed <= 0.1",
+    "message": "Percentage of failed processes should be less than 10%\n  Task: spatial_simulators\n  Method: negative_normal\n  Succeeded processes: 10\n  Attempted processes: 10\n  Percentage failed: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric component 'downstream' % failed",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_failed <= 0.1",
+    "message": "Percentage of failed processes should be less than 10%\n  Task: spatial_simulators\n  Metric component: downstream\n  Succeeded processes: 99\n  Attempted processes: 99\n  Percentage failed: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric component 'ks_statistic_gene_cell' % failed",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_failed <= 0.1",
+    "message": "Percentage of failed processes should be less than 10%\n  Task: spatial_simulators\n  Metric component: ks_statistic_gene_cell\n  Succeeded processes: 99\n  Attempted processes: 99\n  Percentage failed: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric component 'ks_statistic_sc_features' % failed",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_failed <= 0.1",
+    "message": "Percentage of failed processes should be less than 10%\n  Task: spatial_simulators\n  Metric component: ks_statistic_sc_features\n  Succeeded processes: 99\n  Attempted processes: 99\n  Percentage failed: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Dataset `osteosarcoma' number of control methods",
+    "value": 3,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "n_controls != length(control_methods)",
+    "message": "Number of successful control methods for a dataset should equal the number of controls\n  Task: spatial_simulators\n  Dataset: osteosarcoma\n  Succeeded control_methods: 3\n  Total control methods: 3\n  Percentage succeeded: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Dataset `cortex' number of control methods",
+    "value": 3,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "n_controls != length(control_methods)",
+    "message": "Number of successful control methods for a dataset should equal the number of controls\n  Task: spatial_simulators\n  Dataset: cortex\n  Succeeded control_methods: 3\n  Total control methods: 3\n  Percentage succeeded: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Dataset `breast' number of control methods",
+    "value": 3,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "n_controls != length(control_methods)",
+    "message": "Number of successful control methods for a dataset should equal the number of controls\n  Task: spatial_simulators\n  Dataset: breast\n  Succeeded control_methods: 3\n  Total control methods: 3\n  Percentage succeeded: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Dataset `prostate' number of control methods",
+    "value": 3,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "n_controls != length(control_methods)",
+    "message": "Number of successful control methods for a dataset should equal the number of controls\n  Task: spatial_simulators\n  Dataset: prostate\n  Succeeded control_methods: 3\n  Total control methods: 3\n  Percentage succeeded: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Dataset `gastrulation' number of control methods",
+    "value": 3,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "n_controls != length(control_methods)",
+    "message": "Number of successful control methods for a dataset should equal the number of controls\n  Task: spatial_simulators\n  Dataset: gastrulation\n  Succeeded control_methods: 3\n  Total control methods: 3\n  Percentage succeeded: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Dataset `brain' number of control methods",
+    "value": 3,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "n_controls != length(control_methods)",
+    "message": "Number of successful control methods for a dataset should equal the number of controls\n  Task: spatial_simulators\n  Dataset: brain\n  Succeeded control_methods: 3\n  Total control methods: 3\n  Percentage succeeded: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Dataset `pdac' number of control methods",
+    "value": 3,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "n_controls != length(control_methods)",
+    "message": "Number of successful control methods for a dataset should equal the number of controls\n  Task: spatial_simulators\n  Dataset: pdac\n  Succeeded control_methods: 3\n  Total control methods: 3\n  Percentage succeeded: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Dataset `olfactorybulb' number of control methods",
+    "value": 3,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "n_controls != length(control_methods)",
+    "message": "Number of successful control methods for a dataset should equal the number of controls\n  Task: spatial_simulators\n  Dataset: olfactorybulb\n  Succeeded control_methods: 3\n  Total control methods: 3\n  Percentage succeeded: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Dataset `fibrosarcoma' number of control methods",
+    "value": 3,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "n_controls != length(control_methods)",
+    "message": "Number of successful control methods for a dataset should equal the number of controls\n  Task: spatial_simulators\n  Dataset: fibrosarcoma\n  Succeeded control_methods: 3\n  Total control methods: 3\n  Percentage succeeded: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Dataset `hindlimbmuscle' number of control methods",
+    "value": 3,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "n_controls != length(control_methods)",
+    "message": "Number of successful control methods for a dataset should equal the number of controls\n  Task: spatial_simulators\n  Dataset: hindlimbmuscle\n  Succeeded control_methods: 3\n  Total control methods: 3\n  Percentage succeeded: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'clustering_ari' number of control methods",
+    "value": 30,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: clustering_ari\n  Control method scores: 30\n  Expected control method scores: 30\n  Percentage succeeded: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'clustering_nmi' number of control methods",
+    "value": 30,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: clustering_nmi\n  Control method scores: 30\n  Expected control method scores: 30\n  Percentage succeeded: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'svg_recall' number of control methods",
+    "value": 24,
+    "severity": 3,
+    "severity_value": 3,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: svg_recall\n  Control method scores: 24\n  Expected control method scores: 30\n  Percentage succeeded: 80%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'svg_precision' number of control methods",
+    "value": 9,
+    "severity": 3,
+    "severity_value": 3,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: svg_precision\n  Control method scores: 9\n  Expected control method scores: 30\n  Percentage succeeded: 30%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ctdeconvolute_rmse' number of control methods",
+    "value": 30,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: ctdeconvolute_rmse\n  Control method scores: 30\n  Expected control method scores: 30\n  Percentage succeeded: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ctdeconvolute_jsd' number of control methods",
+    "value": 30,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: ctdeconvolute_jsd\n  Control method scores: 30\n  Expected control method scores: 30\n  Percentage succeeded: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'crosscor_mantel' number of control methods",
+    "value": 30,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: crosscor_mantel\n  Control method scores: 30\n  Expected control method scores: 30\n  Percentage succeeded: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'crosscor_cosine' number of control methods",
+    "value": 30,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: crosscor_cosine\n  Control method scores: 30\n  Expected control method scores: 30\n  Percentage succeeded: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_frac_zero_genes_zstat' number of control methods",
+    "value": 0,
+    "severity": 3,
+    "severity_value": 3,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: ks_statistic_frac_zero_genes_zstat\n  Control method scores: 0\n  Expected control method scores: 30\n  Percentage succeeded: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_frac_zero_cells_zstat' number of control methods",
+    "value": 0,
+    "severity": 3,
+    "severity_value": 3,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: ks_statistic_frac_zero_cells_zstat\n  Control method scores: 0\n  Expected control method scores: 30\n  Percentage succeeded: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_lib_size_cells_zstat' number of control methods",
+    "value": 0,
+    "severity": 3,
+    "severity_value": 3,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: ks_statistic_lib_size_cells_zstat\n  Control method scores: 0\n  Expected control method scores: 30\n  Percentage succeeded: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_efflib_size_cells_zstat' number of control methods",
+    "value": 0,
+    "severity": 3,
+    "severity_value": 3,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: ks_statistic_efflib_size_cells_zstat\n  Control method scores: 0\n  Expected control method scores: 30\n  Percentage succeeded: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_tmm_cells_zstat' number of control methods",
+    "value": 0,
+    "severity": 3,
+    "severity_value": 3,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: ks_statistic_tmm_cells_zstat\n  Control method scores: 0\n  Expected control method scores: 30\n  Percentage succeeded: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_scaled_var_cells_zstat' number of control methods",
+    "value": 0,
+    "severity": 3,
+    "severity_value": 3,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: ks_statistic_scaled_var_cells_zstat\n  Control method scores: 0\n  Expected control method scores: 30\n  Percentage succeeded: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_scaled_mean_cells_zstat' number of control methods",
+    "value": 0,
+    "severity": 3,
+    "severity_value": 3,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: ks_statistic_scaled_mean_cells_zstat\n  Control method scores: 0\n  Expected control method scores: 30\n  Percentage succeeded: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_lib_fraczero_cells_zstat' number of control methods",
+    "value": 0,
+    "severity": 3,
+    "severity_value": 3,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: ks_statistic_lib_fraczero_cells_zstat\n  Control method scores: 0\n  Expected control method scores: 30\n  Percentage succeeded: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_pearson_cells_zstat' number of control methods",
+    "value": 0,
+    "severity": 3,
+    "severity_value": 3,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: ks_statistic_pearson_cells_zstat\n  Control method scores: 0\n  Expected control method scores: 30\n  Percentage succeeded: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_scaled_var_genes_zstat' number of control methods",
+    "value": 0,
+    "severity": 3,
+    "severity_value": 3,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: ks_statistic_scaled_var_genes_zstat\n  Control method scores: 0\n  Expected control method scores: 30\n  Percentage succeeded: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_scaled_mean_genes_zstat' number of control methods",
+    "value": 0,
+    "severity": 3,
+    "severity_value": 3,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: ks_statistic_scaled_mean_genes_zstat\n  Control method scores: 0\n  Expected control method scores: 30\n  Percentage succeeded: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_pearson_genes_zstat' number of control methods",
+    "value": 0,
+    "severity": 3,
+    "severity_value": 3,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: ks_statistic_pearson_genes_zstat\n  Control method scores: 0\n  Expected control method scores: 30\n  Percentage succeeded: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_mean_var_genes_zstat' number of control methods",
+    "value": 0,
+    "severity": 3,
+    "severity_value": 3,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: ks_statistic_mean_var_genes_zstat\n  Control method scores: 0\n  Expected control method scores: 30\n  Percentage succeeded: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_mean_fraczero_genes_zstat' number of control methods",
+    "value": 0,
+    "severity": 3,
+    "severity_value": 3,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: ks_statistic_mean_fraczero_genes_zstat\n  Control method scores: 0\n  Expected control method scores: 30\n  Percentage succeeded: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_frac_zero_genes_tstat' number of control methods",
+    "value": 0,
+    "severity": 3,
+    "severity_value": 3,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: ks_statistic_frac_zero_genes_tstat\n  Control method scores: 0\n  Expected control method scores: 30\n  Percentage succeeded: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_frac_zero_cells_tstat' number of control methods",
+    "value": 0,
+    "severity": 3,
+    "severity_value": 3,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: ks_statistic_frac_zero_cells_tstat\n  Control method scores: 0\n  Expected control method scores: 30\n  Percentage succeeded: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_lib_size_cells_tstat' number of control methods",
+    "value": 0,
+    "severity": 3,
+    "severity_value": 3,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: ks_statistic_lib_size_cells_tstat\n  Control method scores: 0\n  Expected control method scores: 30\n  Percentage succeeded: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_efflib_size_cells_tstat' number of control methods",
+    "value": 0,
+    "severity": 3,
+    "severity_value": 3,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: ks_statistic_efflib_size_cells_tstat\n  Control method scores: 0\n  Expected control method scores: 30\n  Percentage succeeded: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_tmm_cells_tstat' number of control methods",
+    "value": 0,
+    "severity": 3,
+    "severity_value": 3,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: ks_statistic_tmm_cells_tstat\n  Control method scores: 0\n  Expected control method scores: 30\n  Percentage succeeded: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_scaled_var_cells_tstat' number of control methods",
+    "value": 0,
+    "severity": 3,
+    "severity_value": 3,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: ks_statistic_scaled_var_cells_tstat\n  Control method scores: 0\n  Expected control method scores: 30\n  Percentage succeeded: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_scaled_mean_cells_tstat' number of control methods",
+    "value": 0,
+    "severity": 3,
+    "severity_value": 3,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: ks_statistic_scaled_mean_cells_tstat\n  Control method scores: 0\n  Expected control method scores: 30\n  Percentage succeeded: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_lib_fraczero_cells_tstat' number of control methods",
+    "value": 0,
+    "severity": 3,
+    "severity_value": 3,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: ks_statistic_lib_fraczero_cells_tstat\n  Control method scores: 0\n  Expected control method scores: 30\n  Percentage succeeded: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_pearson_cells_tstat' number of control methods",
+    "value": 0,
+    "severity": 3,
+    "severity_value": 3,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: ks_statistic_pearson_cells_tstat\n  Control method scores: 0\n  Expected control method scores: 30\n  Percentage succeeded: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_scaled_var_genes_tstat' number of control methods",
+    "value": 0,
+    "severity": 3,
+    "severity_value": 3,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: ks_statistic_scaled_var_genes_tstat\n  Control method scores: 0\n  Expected control method scores: 30\n  Percentage succeeded: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_scaled_mean_genes_tstat' number of control methods",
+    "value": 0,
+    "severity": 3,
+    "severity_value": 3,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: ks_statistic_scaled_mean_genes_tstat\n  Control method scores: 0\n  Expected control method scores: 30\n  Percentage succeeded: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_pearson_genes_tstat' number of control methods",
+    "value": 0,
+    "severity": 3,
+    "severity_value": 3,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: ks_statistic_pearson_genes_tstat\n  Control method scores: 0\n  Expected control method scores: 30\n  Percentage succeeded: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_mean_var_genes_tstat' number of control methods",
+    "value": 0,
+    "severity": 3,
+    "severity_value": 3,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: ks_statistic_mean_var_genes_tstat\n  Control method scores: 0\n  Expected control method scores: 30\n  Percentage succeeded: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_mean_fraczero_genes_tstat' number of control methods",
+    "value": 0,
+    "severity": 3,
+    "severity_value": 3,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: ks_statistic_mean_fraczero_genes_tstat\n  Control method scores: 0\n  Expected control method scores: 30\n  Percentage succeeded: 0%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_L_stats' number of control methods",
+    "value": 30,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: ks_statistic_L_stats\n  Control method scores: 30\n  Expected control method scores: 30\n  Percentage succeeded: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_nn_correlation' number of control methods",
+    "value": 30,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: ks_statistic_nn_correlation\n  Control method scores: 30\n  Expected control method scores: 30\n  Percentage succeeded: 100%\n"
+  },
+  {
+    "category": "Raw results",
+    "label": "Metric 'ks_statistic_morans_I' number of control methods",
+    "value": 30,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "n_controls != length(datasets) * length(control_methods)",
+    "message": "Number of metric scores for control methods should be equal to #datasets × #control_methods\n  Task: spatial_simulators\n  Metric: ks_statistic_morans_I\n  Control method scores: 30\n  Expected control method scores: 30\n  Percentage succeeded: 100%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Metric 'clustering_ari' % outside range",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_outside <= 0.1",
+    "message": "Percentage of scaled scores outside control range should be less than 10%\n  Task: spatial_simulators\n  Metric: clustering_ari\n  Inside range: 99\n  Scaled scores: 99\n  Percentage outside: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Metric 'clustering_ari' worst score % outside range",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_pct_outside <= 0.1",
+    "message": "The worst scaled score should be less than 10% outside the control range\n  Task: spatial_simulators\n  Metric: clustering_ari\n  Worst score: 0.000832639467110741\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Metric 'clustering_ari' best score % outside range",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_pct_outside <= 0.1",
+    "message": "The best scaled score should be less than 10% outside the control range\n  Task: spatial_simulators\n  Metric: clustering_ari\n  Best score: 0.000832639467110741\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'clustering_ari' score for 'negative_normal'",
+    "value": 0.0008,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'negative_normal' performs much worse than controls for metric' clustering_ari'\n  Task: spatial_simulators\n  Method: negative_normal\n  Metric: clustering_ari\n  Worst score: 0.000832639467110741\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'clustering_ari' score for 'negative_normal'",
+    "value": 0.0008,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'negative_normal' performs much better than controls for metric 'clustering_ari'\n  Task: spatial_simulators\n  Method: negative_normal\n  Metric: clustering_ari\n  Best score: 0.000832639467110741\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'clustering_ari' score for 'negative_shuffle'",
+    "value": 0.0008,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'negative_shuffle' performs much worse than controls for metric' clustering_ari'\n  Task: spatial_simulators\n  Method: negative_shuffle\n  Metric: clustering_ari\n  Worst score: 0.000832639467110741\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'clustering_ari' score for 'negative_shuffle'",
+    "value": 0.0008,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'negative_shuffle' performs much better than controls for metric 'clustering_ari'\n  Task: spatial_simulators\n  Method: negative_shuffle\n  Metric: clustering_ari\n  Best score: 0.000832639467110741\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'clustering_ari' score for 'positive'",
+    "value": 0.0008,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'positive' performs much worse than controls for metric' clustering_ari'\n  Task: spatial_simulators\n  Method: positive\n  Metric: clustering_ari\n  Worst score: 0.000832639467110741\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'clustering_ari' score for 'positive'",
+    "value": 0.0008,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'positive' performs much better than controls for metric 'clustering_ari'\n  Task: spatial_simulators\n  Method: positive\n  Metric: clustering_ari\n  Best score: 0.000832639467110741\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'clustering_ari' score for 'scdesign2'",
+    "value": 0.0008,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'scdesign2' performs much worse than controls for metric' clustering_ari'\n  Task: spatial_simulators\n  Method: scdesign2\n  Metric: clustering_ari\n  Worst score: 0.000832639467110741\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'clustering_ari' score for 'scdesign2'",
+    "value": 0.0008,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'scdesign2' performs much better than controls for metric 'clustering_ari'\n  Task: spatial_simulators\n  Method: scdesign2\n  Metric: clustering_ari\n  Best score: 0.000832639467110741\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'clustering_ari' score for 'scdesign3_nb'",
+    "value": 0.0008,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'scdesign3_nb' performs much worse than controls for metric' clustering_ari'\n  Task: spatial_simulators\n  Method: scdesign3_nb\n  Metric: clustering_ari\n  Worst score: 0.000832639467110741\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'clustering_ari' score for 'scdesign3_nb'",
+    "value": 0.0008,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'scdesign3_nb' performs much better than controls for metric 'clustering_ari'\n  Task: spatial_simulators\n  Method: scdesign3_nb\n  Metric: clustering_ari\n  Best score: 0.000832639467110741\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'clustering_ari' score for 'scdesign3_poisson'",
+    "value": 0.0008,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'scdesign3_poisson' performs much worse than controls for metric' clustering_ari'\n  Task: spatial_simulators\n  Method: scdesign3_poisson\n  Metric: clustering_ari\n  Worst score: 0.000832639467110741\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'clustering_ari' score for 'scdesign3_poisson'",
+    "value": 0.0008,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'scdesign3_poisson' performs much better than controls for metric 'clustering_ari'\n  Task: spatial_simulators\n  Method: scdesign3_poisson\n  Metric: clustering_ari\n  Best score: 0.000832639467110741\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'clustering_ari' score for 'sparsim'",
+    "value": 0.0008,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'sparsim' performs much worse than controls for metric' clustering_ari'\n  Task: spatial_simulators\n  Method: sparsim\n  Metric: clustering_ari\n  Worst score: 0.000832639467110741\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'clustering_ari' score for 'sparsim'",
+    "value": 0.0008,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'sparsim' performs much better than controls for metric 'clustering_ari'\n  Task: spatial_simulators\n  Method: sparsim\n  Metric: clustering_ari\n  Best score: 0.000832639467110741\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'clustering_ari' score for 'splatter'",
+    "value": 0.0008,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'splatter' performs much worse than controls for metric' clustering_ari'\n  Task: spatial_simulators\n  Method: splatter\n  Metric: clustering_ari\n  Worst score: 0.000832639467110741\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'clustering_ari' score for 'splatter'",
+    "value": 0.0008,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'splatter' performs much better than controls for metric 'clustering_ari'\n  Task: spatial_simulators\n  Method: splatter\n  Metric: clustering_ari\n  Best score: 0.000832639467110741\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'clustering_ari' score for 'srtsim'",
+    "value": 0.0008,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'srtsim' performs much worse than controls for metric' clustering_ari'\n  Task: spatial_simulators\n  Method: srtsim\n  Metric: clustering_ari\n  Worst score: 0.000832639467110741\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'clustering_ari' score for 'srtsim'",
+    "value": 0.0008,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'srtsim' performs much better than controls for metric 'clustering_ari'\n  Task: spatial_simulators\n  Method: srtsim\n  Metric: clustering_ari\n  Best score: 0.000832639467110741\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'clustering_ari' score for 'symsim'",
+    "value": 0.0008,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'symsim' performs much worse than controls for metric' clustering_ari'\n  Task: spatial_simulators\n  Method: symsim\n  Metric: clustering_ari\n  Worst score: 0.000832639467110741\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'clustering_ari' score for 'symsim'",
+    "value": 0.0008,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'symsim' performs much better than controls for metric 'clustering_ari'\n  Task: spatial_simulators\n  Method: symsim\n  Metric: clustering_ari\n  Best score: 0.000832639467110741\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Metric 'clustering_nmi' % outside range",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_outside <= 0.1",
+    "message": "Percentage of scaled scores outside control range should be less than 10%\n  Task: spatial_simulators\n  Metric: clustering_nmi\n  Inside range: 99\n  Scaled scores: 99\n  Percentage outside: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Metric 'clustering_nmi' worst score % outside range",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_pct_outside <= 0.1",
+    "message": "The worst scaled score should be less than 10% outside the control range\n  Task: spatial_simulators\n  Metric: clustering_nmi\n  Worst score: 0.00124567474048443\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Metric 'clustering_nmi' best score % outside range",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_pct_outside <= 0.1",
+    "message": "The best scaled score should be less than 10% outside the control range\n  Task: spatial_simulators\n  Metric: clustering_nmi\n  Best score: 0.00124567474048443\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'clustering_nmi' score for 'negative_normal'",
+    "value": 0.0012,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'negative_normal' performs much worse than controls for metric' clustering_nmi'\n  Task: spatial_simulators\n  Method: negative_normal\n  Metric: clustering_nmi\n  Worst score: 0.00124567474048443\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'clustering_nmi' score for 'negative_normal'",
+    "value": 0.0012,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'negative_normal' performs much better than controls for metric 'clustering_nmi'\n  Task: spatial_simulators\n  Method: negative_normal\n  Metric: clustering_nmi\n  Best score: 0.00124567474048443\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'clustering_nmi' score for 'negative_shuffle'",
+    "value": 0.0012,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'negative_shuffle' performs much worse than controls for metric' clustering_nmi'\n  Task: spatial_simulators\n  Method: negative_shuffle\n  Metric: clustering_nmi\n  Worst score: 0.00124567474048443\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'clustering_nmi' score for 'negative_shuffle'",
+    "value": 0.0012,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'negative_shuffle' performs much better than controls for metric 'clustering_nmi'\n  Task: spatial_simulators\n  Method: negative_shuffle\n  Metric: clustering_nmi\n  Best score: 0.00124567474048443\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'clustering_nmi' score for 'positive'",
+    "value": 0.0012,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'positive' performs much worse than controls for metric' clustering_nmi'\n  Task: spatial_simulators\n  Method: positive\n  Metric: clustering_nmi\n  Worst score: 0.00124567474048443\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'clustering_nmi' score for 'positive'",
+    "value": 0.0012,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'positive' performs much better than controls for metric 'clustering_nmi'\n  Task: spatial_simulators\n  Method: positive\n  Metric: clustering_nmi\n  Best score: 0.00124567474048443\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'clustering_nmi' score for 'scdesign2'",
+    "value": 0.0012,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'scdesign2' performs much worse than controls for metric' clustering_nmi'\n  Task: spatial_simulators\n  Method: scdesign2\n  Metric: clustering_nmi\n  Worst score: 0.00124567474048443\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'clustering_nmi' score for 'scdesign2'",
+    "value": 0.0012,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'scdesign2' performs much better than controls for metric 'clustering_nmi'\n  Task: spatial_simulators\n  Method: scdesign2\n  Metric: clustering_nmi\n  Best score: 0.00124567474048443\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'clustering_nmi' score for 'scdesign3_nb'",
+    "value": 0.0012,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'scdesign3_nb' performs much worse than controls for metric' clustering_nmi'\n  Task: spatial_simulators\n  Method: scdesign3_nb\n  Metric: clustering_nmi\n  Worst score: 0.00124567474048443\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'clustering_nmi' score for 'scdesign3_nb'",
+    "value": 0.0012,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'scdesign3_nb' performs much better than controls for metric 'clustering_nmi'\n  Task: spatial_simulators\n  Method: scdesign3_nb\n  Metric: clustering_nmi\n  Best score: 0.00124567474048443\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'clustering_nmi' score for 'scdesign3_poisson'",
+    "value": 0.0012,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'scdesign3_poisson' performs much worse than controls for metric' clustering_nmi'\n  Task: spatial_simulators\n  Method: scdesign3_poisson\n  Metric: clustering_nmi\n  Worst score: 0.00124567474048443\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'clustering_nmi' score for 'scdesign3_poisson'",
+    "value": 0.0012,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'scdesign3_poisson' performs much better than controls for metric 'clustering_nmi'\n  Task: spatial_simulators\n  Method: scdesign3_poisson\n  Metric: clustering_nmi\n  Best score: 0.00124567474048443\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'clustering_nmi' score for 'sparsim'",
+    "value": 0.0012,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'sparsim' performs much worse than controls for metric' clustering_nmi'\n  Task: spatial_simulators\n  Method: sparsim\n  Metric: clustering_nmi\n  Worst score: 0.00124567474048443\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'clustering_nmi' score for 'sparsim'",
+    "value": 0.0012,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'sparsim' performs much better than controls for metric 'clustering_nmi'\n  Task: spatial_simulators\n  Method: sparsim\n  Metric: clustering_nmi\n  Best score: 0.00124567474048443\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'clustering_nmi' score for 'splatter'",
+    "value": 0.0012,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'splatter' performs much worse than controls for metric' clustering_nmi'\n  Task: spatial_simulators\n  Method: splatter\n  Metric: clustering_nmi\n  Worst score: 0.00124567474048443\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'clustering_nmi' score for 'splatter'",
+    "value": 0.0012,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'splatter' performs much better than controls for metric 'clustering_nmi'\n  Task: spatial_simulators\n  Method: splatter\n  Metric: clustering_nmi\n  Best score: 0.00124567474048443\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'clustering_nmi' score for 'srtsim'",
+    "value": 0.0012,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'srtsim' performs much worse than controls for metric' clustering_nmi'\n  Task: spatial_simulators\n  Method: srtsim\n  Metric: clustering_nmi\n  Worst score: 0.00124567474048443\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'clustering_nmi' score for 'srtsim'",
+    "value": 0.0012,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'srtsim' performs much better than controls for metric 'clustering_nmi'\n  Task: spatial_simulators\n  Method: srtsim\n  Metric: clustering_nmi\n  Best score: 0.00124567474048443\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'clustering_nmi' score for 'symsim'",
+    "value": 0.0012,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'symsim' performs much worse than controls for metric' clustering_nmi'\n  Task: spatial_simulators\n  Method: symsim\n  Metric: clustering_nmi\n  Worst score: 0.00124567474048443\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'clustering_nmi' score for 'symsim'",
+    "value": 0.0012,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'symsim' performs much better than controls for metric 'clustering_nmi'\n  Task: spatial_simulators\n  Method: symsim\n  Metric: clustering_nmi\n  Best score: 0.00124567474048443\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Metric 'svg_recall' % outside range",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_outside <= 0.1",
+    "message": "Percentage of scaled scores outside control range should be less than 10%\n  Task: spatial_simulators\n  Metric: svg_recall\n  Inside range: 79\n  Scaled scores: 79\n  Percentage outside: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Metric 'svg_recall' worst score % outside range",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_pct_outside <= 0.1",
+    "message": "The worst scaled score should be less than 10% outside the control range\n  Task: spatial_simulators\n  Metric: svg_recall\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Metric 'svg_recall' best score % outside range",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_pct_outside <= 0.1",
+    "message": "The best scaled score should be less than 10% outside the control range\n  Task: spatial_simulators\n  Metric: svg_recall\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'svg_recall' score for 'negative_normal'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'negative_normal' performs much worse than controls for metric' svg_recall'\n  Task: spatial_simulators\n  Method: negative_normal\n  Metric: svg_recall\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'svg_recall' score for 'negative_normal'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'negative_normal' performs much better than controls for metric 'svg_recall'\n  Task: spatial_simulators\n  Method: negative_normal\n  Metric: svg_recall\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'svg_recall' score for 'negative_shuffle'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'negative_shuffle' performs much worse than controls for metric' svg_recall'\n  Task: spatial_simulators\n  Method: negative_shuffle\n  Metric: svg_recall\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'svg_recall' score for 'negative_shuffle'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'negative_shuffle' performs much better than controls for metric 'svg_recall'\n  Task: spatial_simulators\n  Method: negative_shuffle\n  Metric: svg_recall\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'svg_recall' score for 'positive'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'positive' performs much worse than controls for metric' svg_recall'\n  Task: spatial_simulators\n  Method: positive\n  Metric: svg_recall\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'svg_recall' score for 'positive'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'positive' performs much better than controls for metric 'svg_recall'\n  Task: spatial_simulators\n  Method: positive\n  Metric: svg_recall\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'svg_recall' score for 'scdesign2'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'scdesign2' performs much worse than controls for metric' svg_recall'\n  Task: spatial_simulators\n  Method: scdesign2\n  Metric: svg_recall\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'svg_recall' score for 'scdesign2'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'scdesign2' performs much better than controls for metric 'svg_recall'\n  Task: spatial_simulators\n  Method: scdesign2\n  Metric: svg_recall\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'svg_recall' score for 'scdesign3_nb'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'scdesign3_nb' performs much worse than controls for metric' svg_recall'\n  Task: spatial_simulators\n  Method: scdesign3_nb\n  Metric: svg_recall\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'svg_recall' score for 'scdesign3_nb'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'scdesign3_nb' performs much better than controls for metric 'svg_recall'\n  Task: spatial_simulators\n  Method: scdesign3_nb\n  Metric: svg_recall\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'svg_recall' score for 'scdesign3_poisson'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'scdesign3_poisson' performs much worse than controls for metric' svg_recall'\n  Task: spatial_simulators\n  Method: scdesign3_poisson\n  Metric: svg_recall\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'svg_recall' score for 'scdesign3_poisson'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'scdesign3_poisson' performs much better than controls for metric 'svg_recall'\n  Task: spatial_simulators\n  Method: scdesign3_poisson\n  Metric: svg_recall\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'svg_recall' score for 'sparsim'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'sparsim' performs much worse than controls for metric' svg_recall'\n  Task: spatial_simulators\n  Method: sparsim\n  Metric: svg_recall\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'svg_recall' score for 'sparsim'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'sparsim' performs much better than controls for metric 'svg_recall'\n  Task: spatial_simulators\n  Method: sparsim\n  Metric: svg_recall\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'svg_recall' score for 'splatter'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'splatter' performs much worse than controls for metric' svg_recall'\n  Task: spatial_simulators\n  Method: splatter\n  Metric: svg_recall\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'svg_recall' score for 'splatter'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'splatter' performs much better than controls for metric 'svg_recall'\n  Task: spatial_simulators\n  Method: splatter\n  Metric: svg_recall\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'svg_recall' score for 'srtsim'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'srtsim' performs much worse than controls for metric' svg_recall'\n  Task: spatial_simulators\n  Method: srtsim\n  Metric: svg_recall\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'svg_recall' score for 'srtsim'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'srtsim' performs much better than controls for metric 'svg_recall'\n  Task: spatial_simulators\n  Method: srtsim\n  Metric: svg_recall\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'svg_recall' score for 'symsim'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'symsim' performs much worse than controls for metric' svg_recall'\n  Task: spatial_simulators\n  Method: symsim\n  Metric: svg_recall\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'svg_recall' score for 'symsim'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'symsim' performs much better than controls for metric 'svg_recall'\n  Task: spatial_simulators\n  Method: symsim\n  Metric: svg_recall\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Metric 'svg_precision' % outside range",
+    "value": -1,
+    "severity": 3,
+    "severity_value": -1,
+    "condition": "pct_outside <= 0.1",
+    "message": "Percentage of scaled scores outside control range should be less than 10%\n  Task: spatial_simulators\n  Metric: svg_precision\n  Inside range: NA\n  Scaled scores: 65\n  Percentage outside: NA%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Metric 'svg_precision' worst score % outside range",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_pct_outside <= 0.1",
+    "message": "The worst scaled score should be less than 10% outside the control range\n  Task: spatial_simulators\n  Metric: svg_precision\n  Worst score: NA\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Metric 'svg_precision' best score % outside range",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_pct_outside <= 0.1",
+    "message": "The best scaled score should be less than 10% outside the control range\n  Task: spatial_simulators\n  Metric: svg_precision\n  Best score: NA\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'svg_precision' score for 'negative_shuffle'",
+    "value": -1,
+    "severity": 3,
+    "severity_value": -1,
+    "condition": "worst_score < -1",
+    "message": "Method 'negative_shuffle' performs much worse than controls for metric' svg_precision'\n  Task: spatial_simulators\n  Method: negative_shuffle\n  Metric: svg_precision\n  Worst score: NA\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'svg_precision' score for 'negative_shuffle'",
+    "value": -1,
+    "severity": 3,
+    "severity_value": -1,
+    "condition": "best_score > 2",
+    "message": "Method 'negative_shuffle' performs much better than controls for metric 'svg_precision'\n  Task: spatial_simulators\n  Method: negative_shuffle\n  Metric: svg_precision\n  Best score: NA\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'svg_precision' score for 'positive'",
+    "value": -1,
+    "severity": 3,
+    "severity_value": -1,
+    "condition": "worst_score < -1",
+    "message": "Method 'positive' performs much worse than controls for metric' svg_precision'\n  Task: spatial_simulators\n  Method: positive\n  Metric: svg_precision\n  Worst score: NA\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'svg_precision' score for 'positive'",
+    "value": -1,
+    "severity": 3,
+    "severity_value": -1,
+    "condition": "best_score > 2",
+    "message": "Method 'positive' performs much better than controls for metric 'svg_precision'\n  Task: spatial_simulators\n  Method: positive\n  Metric: svg_precision\n  Best score: NA\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'svg_precision' score for 'scdesign2'",
+    "value": -1,
+    "severity": 3,
+    "severity_value": -1,
+    "condition": "worst_score < -1",
+    "message": "Method 'scdesign2' performs much worse than controls for metric' svg_precision'\n  Task: spatial_simulators\n  Method: scdesign2\n  Metric: svg_precision\n  Worst score: NA\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'svg_precision' score for 'scdesign2'",
+    "value": -1,
+    "severity": 3,
+    "severity_value": -1,
+    "condition": "best_score > 2",
+    "message": "Method 'scdesign2' performs much better than controls for metric 'svg_precision'\n  Task: spatial_simulators\n  Method: scdesign2\n  Metric: svg_precision\n  Best score: NA\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'svg_precision' score for 'scdesign3_nb'",
+    "value": -1,
+    "severity": 3,
+    "severity_value": -1,
+    "condition": "worst_score < -1",
+    "message": "Method 'scdesign3_nb' performs much worse than controls for metric' svg_precision'\n  Task: spatial_simulators\n  Method: scdesign3_nb\n  Metric: svg_precision\n  Worst score: NA\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'svg_precision' score for 'scdesign3_nb'",
+    "value": -1,
+    "severity": 3,
+    "severity_value": -1,
+    "condition": "best_score > 2",
+    "message": "Method 'scdesign3_nb' performs much better than controls for metric 'svg_precision'\n  Task: spatial_simulators\n  Method: scdesign3_nb\n  Metric: svg_precision\n  Best score: NA\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'svg_precision' score for 'scdesign3_poisson'",
+    "value": -1,
+    "severity": 3,
+    "severity_value": -1,
+    "condition": "worst_score < -1",
+    "message": "Method 'scdesign3_poisson' performs much worse than controls for metric' svg_precision'\n  Task: spatial_simulators\n  Method: scdesign3_poisson\n  Metric: svg_precision\n  Worst score: NA\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'svg_precision' score for 'scdesign3_poisson'",
+    "value": -1,
+    "severity": 3,
+    "severity_value": -1,
+    "condition": "best_score > 2",
+    "message": "Method 'scdesign3_poisson' performs much better than controls for metric 'svg_precision'\n  Task: spatial_simulators\n  Method: scdesign3_poisson\n  Metric: svg_precision\n  Best score: NA\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'svg_precision' score for 'sparsim'",
+    "value": -1,
+    "severity": 3,
+    "severity_value": -1,
+    "condition": "worst_score < -1",
+    "message": "Method 'sparsim' performs much worse than controls for metric' svg_precision'\n  Task: spatial_simulators\n  Method: sparsim\n  Metric: svg_precision\n  Worst score: NA\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'svg_precision' score for 'sparsim'",
+    "value": -1,
+    "severity": 3,
+    "severity_value": -1,
+    "condition": "best_score > 2",
+    "message": "Method 'sparsim' performs much better than controls for metric 'svg_precision'\n  Task: spatial_simulators\n  Method: sparsim\n  Metric: svg_precision\n  Best score: NA\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'svg_precision' score for 'splatter'",
+    "value": -1,
+    "severity": 3,
+    "severity_value": -1,
+    "condition": "worst_score < -1",
+    "message": "Method 'splatter' performs much worse than controls for metric' svg_precision'\n  Task: spatial_simulators\n  Method: splatter\n  Metric: svg_precision\n  Worst score: NA\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'svg_precision' score for 'splatter'",
+    "value": -1,
+    "severity": 3,
+    "severity_value": -1,
+    "condition": "best_score > 2",
+    "message": "Method 'splatter' performs much better than controls for metric 'svg_precision'\n  Task: spatial_simulators\n  Method: splatter\n  Metric: svg_precision\n  Best score: NA\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'svg_precision' score for 'srtsim'",
+    "value": -1,
+    "severity": 3,
+    "severity_value": -1,
+    "condition": "worst_score < -1",
+    "message": "Method 'srtsim' performs much worse than controls for metric' svg_precision'\n  Task: spatial_simulators\n  Method: srtsim\n  Metric: svg_precision\n  Worst score: NA\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'svg_precision' score for 'srtsim'",
+    "value": -1,
+    "severity": 3,
+    "severity_value": -1,
+    "condition": "best_score > 2",
+    "message": "Method 'srtsim' performs much better than controls for metric 'svg_precision'\n  Task: spatial_simulators\n  Method: srtsim\n  Metric: svg_precision\n  Best score: NA\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'svg_precision' score for 'symsim'",
+    "value": -1,
+    "severity": 3,
+    "severity_value": -1,
+    "condition": "worst_score < -1",
+    "message": "Method 'symsim' performs much worse than controls for metric' svg_precision'\n  Task: spatial_simulators\n  Method: symsim\n  Metric: svg_precision\n  Worst score: NA\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'svg_precision' score for 'symsim'",
+    "value": -1,
+    "severity": 3,
+    "severity_value": -1,
+    "condition": "best_score > 2",
+    "message": "Method 'symsim' performs much better than controls for metric 'svg_precision'\n  Task: spatial_simulators\n  Method: symsim\n  Metric: svg_precision\n  Best score: NA\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Metric 'ctdeconvolute_rmse' % outside range",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_outside <= 0.1",
+    "message": "Percentage of scaled scores outside control range should be less than 10%\n  Task: spatial_simulators\n  Metric: ctdeconvolute_rmse\n  Inside range: 99\n  Scaled scores: 99\n  Percentage outside: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Metric 'ctdeconvolute_rmse' worst score % outside range",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_pct_outside <= 0.1",
+    "message": "The worst scaled score should be less than 10% outside the control range\n  Task: spatial_simulators\n  Metric: ctdeconvolute_rmse\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Metric 'ctdeconvolute_rmse' best score % outside range",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_pct_outside <= 0.1",
+    "message": "The best scaled score should be less than 10% outside the control range\n  Task: spatial_simulators\n  Metric: ctdeconvolute_rmse\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ctdeconvolute_rmse' score for 'negative_normal'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'negative_normal' performs much worse than controls for metric' ctdeconvolute_rmse'\n  Task: spatial_simulators\n  Method: negative_normal\n  Metric: ctdeconvolute_rmse\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ctdeconvolute_rmse' score for 'negative_normal'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'negative_normal' performs much better than controls for metric 'ctdeconvolute_rmse'\n  Task: spatial_simulators\n  Method: negative_normal\n  Metric: ctdeconvolute_rmse\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ctdeconvolute_rmse' score for 'negative_shuffle'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'negative_shuffle' performs much worse than controls for metric' ctdeconvolute_rmse'\n  Task: spatial_simulators\n  Method: negative_shuffle\n  Metric: ctdeconvolute_rmse\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ctdeconvolute_rmse' score for 'negative_shuffle'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'negative_shuffle' performs much better than controls for metric 'ctdeconvolute_rmse'\n  Task: spatial_simulators\n  Method: negative_shuffle\n  Metric: ctdeconvolute_rmse\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ctdeconvolute_rmse' score for 'positive'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'positive' performs much worse than controls for metric' ctdeconvolute_rmse'\n  Task: spatial_simulators\n  Method: positive\n  Metric: ctdeconvolute_rmse\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ctdeconvolute_rmse' score for 'positive'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'positive' performs much better than controls for metric 'ctdeconvolute_rmse'\n  Task: spatial_simulators\n  Method: positive\n  Metric: ctdeconvolute_rmse\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ctdeconvolute_rmse' score for 'scdesign2'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'scdesign2' performs much worse than controls for metric' ctdeconvolute_rmse'\n  Task: spatial_simulators\n  Method: scdesign2\n  Metric: ctdeconvolute_rmse\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ctdeconvolute_rmse' score for 'scdesign2'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'scdesign2' performs much better than controls for metric 'ctdeconvolute_rmse'\n  Task: spatial_simulators\n  Method: scdesign2\n  Metric: ctdeconvolute_rmse\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ctdeconvolute_rmse' score for 'scdesign3_nb'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'scdesign3_nb' performs much worse than controls for metric' ctdeconvolute_rmse'\n  Task: spatial_simulators\n  Method: scdesign3_nb\n  Metric: ctdeconvolute_rmse\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ctdeconvolute_rmse' score for 'scdesign3_nb'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'scdesign3_nb' performs much better than controls for metric 'ctdeconvolute_rmse'\n  Task: spatial_simulators\n  Method: scdesign3_nb\n  Metric: ctdeconvolute_rmse\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ctdeconvolute_rmse' score for 'scdesign3_poisson'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'scdesign3_poisson' performs much worse than controls for metric' ctdeconvolute_rmse'\n  Task: spatial_simulators\n  Method: scdesign3_poisson\n  Metric: ctdeconvolute_rmse\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ctdeconvolute_rmse' score for 'scdesign3_poisson'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'scdesign3_poisson' performs much better than controls for metric 'ctdeconvolute_rmse'\n  Task: spatial_simulators\n  Method: scdesign3_poisson\n  Metric: ctdeconvolute_rmse\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ctdeconvolute_rmse' score for 'sparsim'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'sparsim' performs much worse than controls for metric' ctdeconvolute_rmse'\n  Task: spatial_simulators\n  Method: sparsim\n  Metric: ctdeconvolute_rmse\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ctdeconvolute_rmse' score for 'sparsim'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'sparsim' performs much better than controls for metric 'ctdeconvolute_rmse'\n  Task: spatial_simulators\n  Method: sparsim\n  Metric: ctdeconvolute_rmse\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ctdeconvolute_rmse' score for 'splatter'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'splatter' performs much worse than controls for metric' ctdeconvolute_rmse'\n  Task: spatial_simulators\n  Method: splatter\n  Metric: ctdeconvolute_rmse\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ctdeconvolute_rmse' score for 'splatter'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'splatter' performs much better than controls for metric 'ctdeconvolute_rmse'\n  Task: spatial_simulators\n  Method: splatter\n  Metric: ctdeconvolute_rmse\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ctdeconvolute_rmse' score for 'srtsim'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'srtsim' performs much worse than controls for metric' ctdeconvolute_rmse'\n  Task: spatial_simulators\n  Method: srtsim\n  Metric: ctdeconvolute_rmse\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ctdeconvolute_rmse' score for 'srtsim'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'srtsim' performs much better than controls for metric 'ctdeconvolute_rmse'\n  Task: spatial_simulators\n  Method: srtsim\n  Metric: ctdeconvolute_rmse\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ctdeconvolute_rmse' score for 'symsim'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'symsim' performs much worse than controls for metric' ctdeconvolute_rmse'\n  Task: spatial_simulators\n  Method: symsim\n  Metric: ctdeconvolute_rmse\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ctdeconvolute_rmse' score for 'symsim'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'symsim' performs much better than controls for metric 'ctdeconvolute_rmse'\n  Task: spatial_simulators\n  Method: symsim\n  Metric: ctdeconvolute_rmse\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Metric 'ctdeconvolute_jsd' % outside range",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_outside <= 0.1",
+    "message": "Percentage of scaled scores outside control range should be less than 10%\n  Task: spatial_simulators\n  Metric: ctdeconvolute_jsd\n  Inside range: 99\n  Scaled scores: 99\n  Percentage outside: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Metric 'ctdeconvolute_jsd' worst score % outside range",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_pct_outside <= 0.1",
+    "message": "The worst scaled score should be less than 10% outside the control range\n  Task: spatial_simulators\n  Metric: ctdeconvolute_jsd\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Metric 'ctdeconvolute_jsd' best score % outside range",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_pct_outside <= 0.1",
+    "message": "The best scaled score should be less than 10% outside the control range\n  Task: spatial_simulators\n  Metric: ctdeconvolute_jsd\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ctdeconvolute_jsd' score for 'negative_normal'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'negative_normal' performs much worse than controls for metric' ctdeconvolute_jsd'\n  Task: spatial_simulators\n  Method: negative_normal\n  Metric: ctdeconvolute_jsd\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ctdeconvolute_jsd' score for 'negative_normal'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'negative_normal' performs much better than controls for metric 'ctdeconvolute_jsd'\n  Task: spatial_simulators\n  Method: negative_normal\n  Metric: ctdeconvolute_jsd\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ctdeconvolute_jsd' score for 'negative_shuffle'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'negative_shuffle' performs much worse than controls for metric' ctdeconvolute_jsd'\n  Task: spatial_simulators\n  Method: negative_shuffle\n  Metric: ctdeconvolute_jsd\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ctdeconvolute_jsd' score for 'negative_shuffle'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'negative_shuffle' performs much better than controls for metric 'ctdeconvolute_jsd'\n  Task: spatial_simulators\n  Method: negative_shuffle\n  Metric: ctdeconvolute_jsd\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ctdeconvolute_jsd' score for 'positive'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'positive' performs much worse than controls for metric' ctdeconvolute_jsd'\n  Task: spatial_simulators\n  Method: positive\n  Metric: ctdeconvolute_jsd\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ctdeconvolute_jsd' score for 'positive'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'positive' performs much better than controls for metric 'ctdeconvolute_jsd'\n  Task: spatial_simulators\n  Method: positive\n  Metric: ctdeconvolute_jsd\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ctdeconvolute_jsd' score for 'scdesign2'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'scdesign2' performs much worse than controls for metric' ctdeconvolute_jsd'\n  Task: spatial_simulators\n  Method: scdesign2\n  Metric: ctdeconvolute_jsd\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ctdeconvolute_jsd' score for 'scdesign2'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'scdesign2' performs much better than controls for metric 'ctdeconvolute_jsd'\n  Task: spatial_simulators\n  Method: scdesign2\n  Metric: ctdeconvolute_jsd\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ctdeconvolute_jsd' score for 'scdesign3_nb'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'scdesign3_nb' performs much worse than controls for metric' ctdeconvolute_jsd'\n  Task: spatial_simulators\n  Method: scdesign3_nb\n  Metric: ctdeconvolute_jsd\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ctdeconvolute_jsd' score for 'scdesign3_nb'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'scdesign3_nb' performs much better than controls for metric 'ctdeconvolute_jsd'\n  Task: spatial_simulators\n  Method: scdesign3_nb\n  Metric: ctdeconvolute_jsd\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ctdeconvolute_jsd' score for 'scdesign3_poisson'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'scdesign3_poisson' performs much worse than controls for metric' ctdeconvolute_jsd'\n  Task: spatial_simulators\n  Method: scdesign3_poisson\n  Metric: ctdeconvolute_jsd\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ctdeconvolute_jsd' score for 'scdesign3_poisson'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'scdesign3_poisson' performs much better than controls for metric 'ctdeconvolute_jsd'\n  Task: spatial_simulators\n  Method: scdesign3_poisson\n  Metric: ctdeconvolute_jsd\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ctdeconvolute_jsd' score for 'sparsim'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'sparsim' performs much worse than controls for metric' ctdeconvolute_jsd'\n  Task: spatial_simulators\n  Method: sparsim\n  Metric: ctdeconvolute_jsd\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ctdeconvolute_jsd' score for 'sparsim'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'sparsim' performs much better than controls for metric 'ctdeconvolute_jsd'\n  Task: spatial_simulators\n  Method: sparsim\n  Metric: ctdeconvolute_jsd\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ctdeconvolute_jsd' score for 'splatter'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'splatter' performs much worse than controls for metric' ctdeconvolute_jsd'\n  Task: spatial_simulators\n  Method: splatter\n  Metric: ctdeconvolute_jsd\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ctdeconvolute_jsd' score for 'splatter'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'splatter' performs much better than controls for metric 'ctdeconvolute_jsd'\n  Task: spatial_simulators\n  Method: splatter\n  Metric: ctdeconvolute_jsd\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ctdeconvolute_jsd' score for 'srtsim'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'srtsim' performs much worse than controls for metric' ctdeconvolute_jsd'\n  Task: spatial_simulators\n  Method: srtsim\n  Metric: ctdeconvolute_jsd\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ctdeconvolute_jsd' score for 'srtsim'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'srtsim' performs much better than controls for metric 'ctdeconvolute_jsd'\n  Task: spatial_simulators\n  Method: srtsim\n  Metric: ctdeconvolute_jsd\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ctdeconvolute_jsd' score for 'symsim'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'symsim' performs much worse than controls for metric' ctdeconvolute_jsd'\n  Task: spatial_simulators\n  Method: symsim\n  Metric: ctdeconvolute_jsd\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ctdeconvolute_jsd' score for 'symsim'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'symsim' performs much better than controls for metric 'ctdeconvolute_jsd'\n  Task: spatial_simulators\n  Method: symsim\n  Metric: ctdeconvolute_jsd\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Metric 'crosscor_mantel' % outside range",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_outside <= 0.1",
+    "message": "Percentage of scaled scores outside control range should be less than 10%\n  Task: spatial_simulators\n  Metric: crosscor_mantel\n  Inside range: 99\n  Scaled scores: 99\n  Percentage outside: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Metric 'crosscor_mantel' worst score % outside range",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_pct_outside <= 0.1",
+    "message": "The worst scaled score should be less than 10% outside the control range\n  Task: spatial_simulators\n  Metric: crosscor_mantel\n  Worst score: 0.00302533719904198\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Metric 'crosscor_mantel' best score % outside range",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_pct_outside <= 0.1",
+    "message": "The best scaled score should be less than 10% outside the control range\n  Task: spatial_simulators\n  Metric: crosscor_mantel\n  Best score: 0.00302533719904198\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'crosscor_mantel' score for 'negative_normal'",
+    "value": 0.003,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'negative_normal' performs much worse than controls for metric' crosscor_mantel'\n  Task: spatial_simulators\n  Method: negative_normal\n  Metric: crosscor_mantel\n  Worst score: 0.00302533719904198\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'crosscor_mantel' score for 'negative_normal'",
+    "value": 0.003,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'negative_normal' performs much better than controls for metric 'crosscor_mantel'\n  Task: spatial_simulators\n  Method: negative_normal\n  Metric: crosscor_mantel\n  Best score: 0.00302533719904198\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'crosscor_mantel' score for 'negative_shuffle'",
+    "value": 0.003,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'negative_shuffle' performs much worse than controls for metric' crosscor_mantel'\n  Task: spatial_simulators\n  Method: negative_shuffle\n  Metric: crosscor_mantel\n  Worst score: 0.00302533719904198\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'crosscor_mantel' score for 'negative_shuffle'",
+    "value": 0.003,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'negative_shuffle' performs much better than controls for metric 'crosscor_mantel'\n  Task: spatial_simulators\n  Method: negative_shuffle\n  Metric: crosscor_mantel\n  Best score: 0.00302533719904198\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'crosscor_mantel' score for 'positive'",
+    "value": 0.003,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'positive' performs much worse than controls for metric' crosscor_mantel'\n  Task: spatial_simulators\n  Method: positive\n  Metric: crosscor_mantel\n  Worst score: 0.00302533719904198\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'crosscor_mantel' score for 'positive'",
+    "value": 0.003,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'positive' performs much better than controls for metric 'crosscor_mantel'\n  Task: spatial_simulators\n  Method: positive\n  Metric: crosscor_mantel\n  Best score: 0.00302533719904198\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'crosscor_mantel' score for 'scdesign2'",
+    "value": 0.003,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'scdesign2' performs much worse than controls for metric' crosscor_mantel'\n  Task: spatial_simulators\n  Method: scdesign2\n  Metric: crosscor_mantel\n  Worst score: 0.00302533719904198\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'crosscor_mantel' score for 'scdesign2'",
+    "value": 0.003,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'scdesign2' performs much better than controls for metric 'crosscor_mantel'\n  Task: spatial_simulators\n  Method: scdesign2\n  Metric: crosscor_mantel\n  Best score: 0.00302533719904198\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'crosscor_mantel' score for 'scdesign3_nb'",
+    "value": 0.003,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'scdesign3_nb' performs much worse than controls for metric' crosscor_mantel'\n  Task: spatial_simulators\n  Method: scdesign3_nb\n  Metric: crosscor_mantel\n  Worst score: 0.00302533719904198\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'crosscor_mantel' score for 'scdesign3_nb'",
+    "value": 0.003,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'scdesign3_nb' performs much better than controls for metric 'crosscor_mantel'\n  Task: spatial_simulators\n  Method: scdesign3_nb\n  Metric: crosscor_mantel\n  Best score: 0.00302533719904198\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'crosscor_mantel' score for 'scdesign3_poisson'",
+    "value": 0.003,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'scdesign3_poisson' performs much worse than controls for metric' crosscor_mantel'\n  Task: spatial_simulators\n  Method: scdesign3_poisson\n  Metric: crosscor_mantel\n  Worst score: 0.00302533719904198\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'crosscor_mantel' score for 'scdesign3_poisson'",
+    "value": 0.003,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'scdesign3_poisson' performs much better than controls for metric 'crosscor_mantel'\n  Task: spatial_simulators\n  Method: scdesign3_poisson\n  Metric: crosscor_mantel\n  Best score: 0.00302533719904198\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'crosscor_mantel' score for 'sparsim'",
+    "value": 0.003,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'sparsim' performs much worse than controls for metric' crosscor_mantel'\n  Task: spatial_simulators\n  Method: sparsim\n  Metric: crosscor_mantel\n  Worst score: 0.00302533719904198\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'crosscor_mantel' score for 'sparsim'",
+    "value": 0.003,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'sparsim' performs much better than controls for metric 'crosscor_mantel'\n  Task: spatial_simulators\n  Method: sparsim\n  Metric: crosscor_mantel\n  Best score: 0.00302533719904198\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'crosscor_mantel' score for 'splatter'",
+    "value": 0.003,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'splatter' performs much worse than controls for metric' crosscor_mantel'\n  Task: spatial_simulators\n  Method: splatter\n  Metric: crosscor_mantel\n  Worst score: 0.00302533719904198\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'crosscor_mantel' score for 'splatter'",
+    "value": 0.003,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'splatter' performs much better than controls for metric 'crosscor_mantel'\n  Task: spatial_simulators\n  Method: splatter\n  Metric: crosscor_mantel\n  Best score: 0.00302533719904198\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'crosscor_mantel' score for 'srtsim'",
+    "value": 0.003,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'srtsim' performs much worse than controls for metric' crosscor_mantel'\n  Task: spatial_simulators\n  Method: srtsim\n  Metric: crosscor_mantel\n  Worst score: 0.00302533719904198\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'crosscor_mantel' score for 'srtsim'",
+    "value": 0.003,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'srtsim' performs much better than controls for metric 'crosscor_mantel'\n  Task: spatial_simulators\n  Method: srtsim\n  Metric: crosscor_mantel\n  Best score: 0.00302533719904198\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'crosscor_mantel' score for 'symsim'",
+    "value": 0.003,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'symsim' performs much worse than controls for metric' crosscor_mantel'\n  Task: spatial_simulators\n  Method: symsim\n  Metric: crosscor_mantel\n  Worst score: 0.00302533719904198\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'crosscor_mantel' score for 'symsim'",
+    "value": 0.003,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'symsim' performs much better than controls for metric 'crosscor_mantel'\n  Task: spatial_simulators\n  Method: symsim\n  Metric: crosscor_mantel\n  Best score: 0.00302533719904198\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Metric 'crosscor_cosine' % outside range",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_outside <= 0.1",
+    "message": "Percentage of scaled scores outside control range should be less than 10%\n  Task: spatial_simulators\n  Metric: crosscor_cosine\n  Inside range: 68\n  Scaled scores: 68\n  Percentage outside: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Metric 'crosscor_cosine' worst score % outside range",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_pct_outside <= 0.1",
+    "message": "The worst scaled score should be less than 10% outside the control range\n  Task: spatial_simulators\n  Metric: crosscor_cosine\n  Worst score: 0.00305343511450376\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Metric 'crosscor_cosine' best score % outside range",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_pct_outside <= 0.1",
+    "message": "The best scaled score should be less than 10% outside the control range\n  Task: spatial_simulators\n  Metric: crosscor_cosine\n  Best score: 0.00305343511450376\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'crosscor_cosine' score for 'negative_normal'",
+    "value": 0.0031,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'negative_normal' performs much worse than controls for metric' crosscor_cosine'\n  Task: spatial_simulators\n  Method: negative_normal\n  Metric: crosscor_cosine\n  Worst score: 0.00305343511450376\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'crosscor_cosine' score for 'negative_normal'",
+    "value": 0.0031,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'negative_normal' performs much better than controls for metric 'crosscor_cosine'\n  Task: spatial_simulators\n  Method: negative_normal\n  Metric: crosscor_cosine\n  Best score: 0.00305343511450376\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'crosscor_cosine' score for 'negative_shuffle'",
+    "value": 0.0031,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'negative_shuffle' performs much worse than controls for metric' crosscor_cosine'\n  Task: spatial_simulators\n  Method: negative_shuffle\n  Metric: crosscor_cosine\n  Worst score: 0.00305343511450376\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'crosscor_cosine' score for 'negative_shuffle'",
+    "value": 0.0031,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'negative_shuffle' performs much better than controls for metric 'crosscor_cosine'\n  Task: spatial_simulators\n  Method: negative_shuffle\n  Metric: crosscor_cosine\n  Best score: 0.00305343511450376\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'crosscor_cosine' score for 'positive'",
+    "value": 0.0031,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'positive' performs much worse than controls for metric' crosscor_cosine'\n  Task: spatial_simulators\n  Method: positive\n  Metric: crosscor_cosine\n  Worst score: 0.00305343511450376\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'crosscor_cosine' score for 'positive'",
+    "value": 0.0031,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'positive' performs much better than controls for metric 'crosscor_cosine'\n  Task: spatial_simulators\n  Method: positive\n  Metric: crosscor_cosine\n  Best score: 0.00305343511450376\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'crosscor_cosine' score for 'scdesign2'",
+    "value": 0.0031,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'scdesign2' performs much worse than controls for metric' crosscor_cosine'\n  Task: spatial_simulators\n  Method: scdesign2\n  Metric: crosscor_cosine\n  Worst score: 0.00305343511450376\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'crosscor_cosine' score for 'scdesign2'",
+    "value": 0.0031,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'scdesign2' performs much better than controls for metric 'crosscor_cosine'\n  Task: spatial_simulators\n  Method: scdesign2\n  Metric: crosscor_cosine\n  Best score: 0.00305343511450376\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'crosscor_cosine' score for 'scdesign3_nb'",
+    "value": 0.0031,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'scdesign3_nb' performs much worse than controls for metric' crosscor_cosine'\n  Task: spatial_simulators\n  Method: scdesign3_nb\n  Metric: crosscor_cosine\n  Worst score: 0.00305343511450376\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'crosscor_cosine' score for 'scdesign3_nb'",
+    "value": 0.0031,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'scdesign3_nb' performs much better than controls for metric 'crosscor_cosine'\n  Task: spatial_simulators\n  Method: scdesign3_nb\n  Metric: crosscor_cosine\n  Best score: 0.00305343511450376\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'crosscor_cosine' score for 'scdesign3_poisson'",
+    "value": 0.0031,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'scdesign3_poisson' performs much worse than controls for metric' crosscor_cosine'\n  Task: spatial_simulators\n  Method: scdesign3_poisson\n  Metric: crosscor_cosine\n  Worst score: 0.00305343511450376\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'crosscor_cosine' score for 'scdesign3_poisson'",
+    "value": 0.0031,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'scdesign3_poisson' performs much better than controls for metric 'crosscor_cosine'\n  Task: spatial_simulators\n  Method: scdesign3_poisson\n  Metric: crosscor_cosine\n  Best score: 0.00305343511450376\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'crosscor_cosine' score for 'sparsim'",
+    "value": 0.0031,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'sparsim' performs much worse than controls for metric' crosscor_cosine'\n  Task: spatial_simulators\n  Method: sparsim\n  Metric: crosscor_cosine\n  Worst score: 0.00305343511450376\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'crosscor_cosine' score for 'sparsim'",
+    "value": 0.0031,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'sparsim' performs much better than controls for metric 'crosscor_cosine'\n  Task: spatial_simulators\n  Method: sparsim\n  Metric: crosscor_cosine\n  Best score: 0.00305343511450376\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'crosscor_cosine' score for 'splatter'",
+    "value": 0.0031,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'splatter' performs much worse than controls for metric' crosscor_cosine'\n  Task: spatial_simulators\n  Method: splatter\n  Metric: crosscor_cosine\n  Worst score: 0.00305343511450376\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'crosscor_cosine' score for 'splatter'",
+    "value": 0.0031,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'splatter' performs much better than controls for metric 'crosscor_cosine'\n  Task: spatial_simulators\n  Method: splatter\n  Metric: crosscor_cosine\n  Best score: 0.00305343511450376\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'crosscor_cosine' score for 'srtsim'",
+    "value": 0.0031,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'srtsim' performs much worse than controls for metric' crosscor_cosine'\n  Task: spatial_simulators\n  Method: srtsim\n  Metric: crosscor_cosine\n  Worst score: 0.00305343511450376\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'crosscor_cosine' score for 'srtsim'",
+    "value": 0.0031,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'srtsim' performs much better than controls for metric 'crosscor_cosine'\n  Task: spatial_simulators\n  Method: srtsim\n  Metric: crosscor_cosine\n  Best score: 0.00305343511450376\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'crosscor_cosine' score for 'symsim'",
+    "value": 0.0031,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'symsim' performs much worse than controls for metric' crosscor_cosine'\n  Task: spatial_simulators\n  Method: symsim\n  Metric: crosscor_cosine\n  Worst score: 0.00305343511450376\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'crosscor_cosine' score for 'symsim'",
+    "value": 0.0031,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'symsim' performs much better than controls for metric 'crosscor_cosine'\n  Task: spatial_simulators\n  Method: symsim\n  Metric: crosscor_cosine\n  Best score: 0.00305343511450376\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Metric 'ks_statistic_L_stats' % outside range",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_outside <= 0.1",
+    "message": "Percentage of scaled scores outside control range should be less than 10%\n  Task: spatial_simulators\n  Metric: ks_statistic_L_stats\n  Inside range: 99\n  Scaled scores: 99\n  Percentage outside: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Metric 'ks_statistic_L_stats' worst score % outside range",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_pct_outside <= 0.1",
+    "message": "The worst scaled score should be less than 10% outside the control range\n  Task: spatial_simulators\n  Metric: ks_statistic_L_stats\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Metric 'ks_statistic_L_stats' best score % outside range",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_pct_outside <= 0.1",
+    "message": "The best scaled score should be less than 10% outside the control range\n  Task: spatial_simulators\n  Metric: ks_statistic_L_stats\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ks_statistic_L_stats' score for 'negative_normal'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'negative_normal' performs much worse than controls for metric' ks_statistic_L_stats'\n  Task: spatial_simulators\n  Method: negative_normal\n  Metric: ks_statistic_L_stats\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ks_statistic_L_stats' score for 'negative_normal'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'negative_normal' performs much better than controls for metric 'ks_statistic_L_stats'\n  Task: spatial_simulators\n  Method: negative_normal\n  Metric: ks_statistic_L_stats\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ks_statistic_L_stats' score for 'negative_shuffle'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'negative_shuffle' performs much worse than controls for metric' ks_statistic_L_stats'\n  Task: spatial_simulators\n  Method: negative_shuffle\n  Metric: ks_statistic_L_stats\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ks_statistic_L_stats' score for 'negative_shuffle'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'negative_shuffle' performs much better than controls for metric 'ks_statistic_L_stats'\n  Task: spatial_simulators\n  Method: negative_shuffle\n  Metric: ks_statistic_L_stats\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ks_statistic_L_stats' score for 'positive'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'positive' performs much worse than controls for metric' ks_statistic_L_stats'\n  Task: spatial_simulators\n  Method: positive\n  Metric: ks_statistic_L_stats\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ks_statistic_L_stats' score for 'positive'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'positive' performs much better than controls for metric 'ks_statistic_L_stats'\n  Task: spatial_simulators\n  Method: positive\n  Metric: ks_statistic_L_stats\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ks_statistic_L_stats' score for 'scdesign2'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'scdesign2' performs much worse than controls for metric' ks_statistic_L_stats'\n  Task: spatial_simulators\n  Method: scdesign2\n  Metric: ks_statistic_L_stats\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ks_statistic_L_stats' score for 'scdesign2'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'scdesign2' performs much better than controls for metric 'ks_statistic_L_stats'\n  Task: spatial_simulators\n  Method: scdesign2\n  Metric: ks_statistic_L_stats\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ks_statistic_L_stats' score for 'scdesign3_nb'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'scdesign3_nb' performs much worse than controls for metric' ks_statistic_L_stats'\n  Task: spatial_simulators\n  Method: scdesign3_nb\n  Metric: ks_statistic_L_stats\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ks_statistic_L_stats' score for 'scdesign3_nb'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'scdesign3_nb' performs much better than controls for metric 'ks_statistic_L_stats'\n  Task: spatial_simulators\n  Method: scdesign3_nb\n  Metric: ks_statistic_L_stats\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ks_statistic_L_stats' score for 'scdesign3_poisson'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'scdesign3_poisson' performs much worse than controls for metric' ks_statistic_L_stats'\n  Task: spatial_simulators\n  Method: scdesign3_poisson\n  Metric: ks_statistic_L_stats\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ks_statistic_L_stats' score for 'scdesign3_poisson'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'scdesign3_poisson' performs much better than controls for metric 'ks_statistic_L_stats'\n  Task: spatial_simulators\n  Method: scdesign3_poisson\n  Metric: ks_statistic_L_stats\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ks_statistic_L_stats' score for 'sparsim'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'sparsim' performs much worse than controls for metric' ks_statistic_L_stats'\n  Task: spatial_simulators\n  Method: sparsim\n  Metric: ks_statistic_L_stats\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ks_statistic_L_stats' score for 'sparsim'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'sparsim' performs much better than controls for metric 'ks_statistic_L_stats'\n  Task: spatial_simulators\n  Method: sparsim\n  Metric: ks_statistic_L_stats\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ks_statistic_L_stats' score for 'splatter'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'splatter' performs much worse than controls for metric' ks_statistic_L_stats'\n  Task: spatial_simulators\n  Method: splatter\n  Metric: ks_statistic_L_stats\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ks_statistic_L_stats' score for 'splatter'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'splatter' performs much better than controls for metric 'ks_statistic_L_stats'\n  Task: spatial_simulators\n  Method: splatter\n  Metric: ks_statistic_L_stats\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ks_statistic_L_stats' score for 'srtsim'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'srtsim' performs much worse than controls for metric' ks_statistic_L_stats'\n  Task: spatial_simulators\n  Method: srtsim\n  Metric: ks_statistic_L_stats\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ks_statistic_L_stats' score for 'srtsim'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'srtsim' performs much better than controls for metric 'ks_statistic_L_stats'\n  Task: spatial_simulators\n  Method: srtsim\n  Metric: ks_statistic_L_stats\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ks_statistic_L_stats' score for 'symsim'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'symsim' performs much worse than controls for metric' ks_statistic_L_stats'\n  Task: spatial_simulators\n  Method: symsim\n  Metric: ks_statistic_L_stats\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ks_statistic_L_stats' score for 'symsim'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'symsim' performs much better than controls for metric 'ks_statistic_L_stats'\n  Task: spatial_simulators\n  Method: symsim\n  Metric: ks_statistic_L_stats\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Metric 'ks_statistic_nn_correlation' % outside range",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_outside <= 0.1",
+    "message": "Percentage of scaled scores outside control range should be less than 10%\n  Task: spatial_simulators\n  Metric: ks_statistic_nn_correlation\n  Inside range: 99\n  Scaled scores: 99\n  Percentage outside: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Metric 'ks_statistic_nn_correlation' worst score % outside range",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_pct_outside <= 0.1",
+    "message": "The worst scaled score should be less than 10% outside the control range\n  Task: spatial_simulators\n  Metric: ks_statistic_nn_correlation\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Metric 'ks_statistic_nn_correlation' best score % outside range",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_pct_outside <= 0.1",
+    "message": "The best scaled score should be less than 10% outside the control range\n  Task: spatial_simulators\n  Metric: ks_statistic_nn_correlation\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ks_statistic_nn_correlation' score for 'negative_normal'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'negative_normal' performs much worse than controls for metric' ks_statistic_nn_correlation'\n  Task: spatial_simulators\n  Method: negative_normal\n  Metric: ks_statistic_nn_correlation\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ks_statistic_nn_correlation' score for 'negative_normal'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'negative_normal' performs much better than controls for metric 'ks_statistic_nn_correlation'\n  Task: spatial_simulators\n  Method: negative_normal\n  Metric: ks_statistic_nn_correlation\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ks_statistic_nn_correlation' score for 'negative_shuffle'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'negative_shuffle' performs much worse than controls for metric' ks_statistic_nn_correlation'\n  Task: spatial_simulators\n  Method: negative_shuffle\n  Metric: ks_statistic_nn_correlation\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ks_statistic_nn_correlation' score for 'negative_shuffle'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'negative_shuffle' performs much better than controls for metric 'ks_statistic_nn_correlation'\n  Task: spatial_simulators\n  Method: negative_shuffle\n  Metric: ks_statistic_nn_correlation\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ks_statistic_nn_correlation' score for 'positive'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'positive' performs much worse than controls for metric' ks_statistic_nn_correlation'\n  Task: spatial_simulators\n  Method: positive\n  Metric: ks_statistic_nn_correlation\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ks_statistic_nn_correlation' score for 'positive'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'positive' performs much better than controls for metric 'ks_statistic_nn_correlation'\n  Task: spatial_simulators\n  Method: positive\n  Metric: ks_statistic_nn_correlation\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ks_statistic_nn_correlation' score for 'scdesign2'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'scdesign2' performs much worse than controls for metric' ks_statistic_nn_correlation'\n  Task: spatial_simulators\n  Method: scdesign2\n  Metric: ks_statistic_nn_correlation\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ks_statistic_nn_correlation' score for 'scdesign2'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'scdesign2' performs much better than controls for metric 'ks_statistic_nn_correlation'\n  Task: spatial_simulators\n  Method: scdesign2\n  Metric: ks_statistic_nn_correlation\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ks_statistic_nn_correlation' score for 'scdesign3_nb'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'scdesign3_nb' performs much worse than controls for metric' ks_statistic_nn_correlation'\n  Task: spatial_simulators\n  Method: scdesign3_nb\n  Metric: ks_statistic_nn_correlation\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ks_statistic_nn_correlation' score for 'scdesign3_nb'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'scdesign3_nb' performs much better than controls for metric 'ks_statistic_nn_correlation'\n  Task: spatial_simulators\n  Method: scdesign3_nb\n  Metric: ks_statistic_nn_correlation\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ks_statistic_nn_correlation' score for 'scdesign3_poisson'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'scdesign3_poisson' performs much worse than controls for metric' ks_statistic_nn_correlation'\n  Task: spatial_simulators\n  Method: scdesign3_poisson\n  Metric: ks_statistic_nn_correlation\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ks_statistic_nn_correlation' score for 'scdesign3_poisson'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'scdesign3_poisson' performs much better than controls for metric 'ks_statistic_nn_correlation'\n  Task: spatial_simulators\n  Method: scdesign3_poisson\n  Metric: ks_statistic_nn_correlation\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ks_statistic_nn_correlation' score for 'sparsim'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'sparsim' performs much worse than controls for metric' ks_statistic_nn_correlation'\n  Task: spatial_simulators\n  Method: sparsim\n  Metric: ks_statistic_nn_correlation\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ks_statistic_nn_correlation' score for 'sparsim'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'sparsim' performs much better than controls for metric 'ks_statistic_nn_correlation'\n  Task: spatial_simulators\n  Method: sparsim\n  Metric: ks_statistic_nn_correlation\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ks_statistic_nn_correlation' score for 'splatter'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'splatter' performs much worse than controls for metric' ks_statistic_nn_correlation'\n  Task: spatial_simulators\n  Method: splatter\n  Metric: ks_statistic_nn_correlation\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ks_statistic_nn_correlation' score for 'splatter'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'splatter' performs much better than controls for metric 'ks_statistic_nn_correlation'\n  Task: spatial_simulators\n  Method: splatter\n  Metric: ks_statistic_nn_correlation\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ks_statistic_nn_correlation' score for 'srtsim'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'srtsim' performs much worse than controls for metric' ks_statistic_nn_correlation'\n  Task: spatial_simulators\n  Method: srtsim\n  Metric: ks_statistic_nn_correlation\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ks_statistic_nn_correlation' score for 'srtsim'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'srtsim' performs much better than controls for metric 'ks_statistic_nn_correlation'\n  Task: spatial_simulators\n  Method: srtsim\n  Metric: ks_statistic_nn_correlation\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ks_statistic_nn_correlation' score for 'symsim'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'symsim' performs much worse than controls for metric' ks_statistic_nn_correlation'\n  Task: spatial_simulators\n  Method: symsim\n  Metric: ks_statistic_nn_correlation\n  Worst score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ks_statistic_nn_correlation' score for 'symsim'",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'symsim' performs much better than controls for metric 'ks_statistic_nn_correlation'\n  Task: spatial_simulators\n  Method: symsim\n  Metric: ks_statistic_nn_correlation\n  Best score: 0\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Metric 'ks_statistic_morans_I' % outside range",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "pct_outside <= 0.1",
+    "message": "Percentage of scaled scores outside control range should be less than 10%\n  Task: spatial_simulators\n  Metric: ks_statistic_morans_I\n  Inside range: 99\n  Scaled scores: 99\n  Percentage outside: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Metric 'ks_statistic_morans_I' worst score % outside range",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_pct_outside <= 0.1",
+    "message": "The worst scaled score should be less than 10% outside the control range\n  Task: spatial_simulators\n  Metric: ks_statistic_morans_I\n  Worst score: 0.297772261057033\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Metric 'ks_statistic_morans_I' best score % outside range",
+    "value": 0,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_pct_outside <= 0.1",
+    "message": "The best scaled score should be less than 10% outside the control range\n  Task: spatial_simulators\n  Metric: ks_statistic_morans_I\n  Best score: 0.297772261057033\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ks_statistic_morans_I' score for 'negative_normal'",
+    "value": 0.2978,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'negative_normal' performs much worse than controls for metric' ks_statistic_morans_I'\n  Task: spatial_simulators\n  Method: negative_normal\n  Metric: ks_statistic_morans_I\n  Worst score: 0.297772261057033\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ks_statistic_morans_I' score for 'negative_normal'",
+    "value": 0.2978,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'negative_normal' performs much better than controls for metric 'ks_statistic_morans_I'\n  Task: spatial_simulators\n  Method: negative_normal\n  Metric: ks_statistic_morans_I\n  Best score: 0.297772261057033\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ks_statistic_morans_I' score for 'negative_shuffle'",
+    "value": 0.2978,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'negative_shuffle' performs much worse than controls for metric' ks_statistic_morans_I'\n  Task: spatial_simulators\n  Method: negative_shuffle\n  Metric: ks_statistic_morans_I\n  Worst score: 0.297772261057033\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ks_statistic_morans_I' score for 'negative_shuffle'",
+    "value": 0.2978,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'negative_shuffle' performs much better than controls for metric 'ks_statistic_morans_I'\n  Task: spatial_simulators\n  Method: negative_shuffle\n  Metric: ks_statistic_morans_I\n  Best score: 0.297772261057033\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ks_statistic_morans_I' score for 'positive'",
+    "value": 0.2978,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'positive' performs much worse than controls for metric' ks_statistic_morans_I'\n  Task: spatial_simulators\n  Method: positive\n  Metric: ks_statistic_morans_I\n  Worst score: 0.297772261057033\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ks_statistic_morans_I' score for 'positive'",
+    "value": 0.2978,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'positive' performs much better than controls for metric 'ks_statistic_morans_I'\n  Task: spatial_simulators\n  Method: positive\n  Metric: ks_statistic_morans_I\n  Best score: 0.297772261057033\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ks_statistic_morans_I' score for 'scdesign2'",
+    "value": 0.2978,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'scdesign2' performs much worse than controls for metric' ks_statistic_morans_I'\n  Task: spatial_simulators\n  Method: scdesign2\n  Metric: ks_statistic_morans_I\n  Worst score: 0.297772261057033\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ks_statistic_morans_I' score for 'scdesign2'",
+    "value": 0.2978,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'scdesign2' performs much better than controls for metric 'ks_statistic_morans_I'\n  Task: spatial_simulators\n  Method: scdesign2\n  Metric: ks_statistic_morans_I\n  Best score: 0.297772261057033\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ks_statistic_morans_I' score for 'scdesign3_nb'",
+    "value": 0.2978,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'scdesign3_nb' performs much worse than controls for metric' ks_statistic_morans_I'\n  Task: spatial_simulators\n  Method: scdesign3_nb\n  Metric: ks_statistic_morans_I\n  Worst score: 0.297772261057033\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ks_statistic_morans_I' score for 'scdesign3_nb'",
+    "value": 0.2978,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'scdesign3_nb' performs much better than controls for metric 'ks_statistic_morans_I'\n  Task: spatial_simulators\n  Method: scdesign3_nb\n  Metric: ks_statistic_morans_I\n  Best score: 0.297772261057033\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ks_statistic_morans_I' score for 'scdesign3_poisson'",
+    "value": 0.2978,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'scdesign3_poisson' performs much worse than controls for metric' ks_statistic_morans_I'\n  Task: spatial_simulators\n  Method: scdesign3_poisson\n  Metric: ks_statistic_morans_I\n  Worst score: 0.297772261057033\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ks_statistic_morans_I' score for 'scdesign3_poisson'",
+    "value": 0.2978,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'scdesign3_poisson' performs much better than controls for metric 'ks_statistic_morans_I'\n  Task: spatial_simulators\n  Method: scdesign3_poisson\n  Metric: ks_statistic_morans_I\n  Best score: 0.297772261057033\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ks_statistic_morans_I' score for 'sparsim'",
+    "value": 0.2978,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'sparsim' performs much worse than controls for metric' ks_statistic_morans_I'\n  Task: spatial_simulators\n  Method: sparsim\n  Metric: ks_statistic_morans_I\n  Worst score: 0.297772261057033\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ks_statistic_morans_I' score for 'sparsim'",
+    "value": 0.2978,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'sparsim' performs much better than controls for metric 'ks_statistic_morans_I'\n  Task: spatial_simulators\n  Method: sparsim\n  Metric: ks_statistic_morans_I\n  Best score: 0.297772261057033\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ks_statistic_morans_I' score for 'splatter'",
+    "value": 0.2978,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'splatter' performs much worse than controls for metric' ks_statistic_morans_I'\n  Task: spatial_simulators\n  Method: splatter\n  Metric: ks_statistic_morans_I\n  Worst score: 0.297772261057033\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ks_statistic_morans_I' score for 'splatter'",
+    "value": 0.2978,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'splatter' performs much better than controls for metric 'ks_statistic_morans_I'\n  Task: spatial_simulators\n  Method: splatter\n  Metric: ks_statistic_morans_I\n  Best score: 0.297772261057033\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ks_statistic_morans_I' score for 'srtsim'",
+    "value": 0.2978,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'srtsim' performs much worse than controls for metric' ks_statistic_morans_I'\n  Task: spatial_simulators\n  Method: srtsim\n  Metric: ks_statistic_morans_I\n  Worst score: 0.297772261057033\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ks_statistic_morans_I' score for 'srtsim'",
+    "value": 0.2978,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'srtsim' performs much better than controls for metric 'ks_statistic_morans_I'\n  Task: spatial_simulators\n  Method: srtsim\n  Metric: ks_statistic_morans_I\n  Best score: 0.297772261057033\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Worst 'ks_statistic_morans_I' score for 'symsim'",
+    "value": 0.2978,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "worst_score < -1",
+    "message": "Method 'symsim' performs much worse than controls for metric' ks_statistic_morans_I'\n  Task: spatial_simulators\n  Method: symsim\n  Metric: ks_statistic_morans_I\n  Worst score: 0.297772261057033\n  Percentage outside range: 0%\n"
+  },
+  {
+    "category": "Scaling",
+    "label": "Best 'ks_statistic_morans_I' score for 'symsim'",
+    "value": 0.2978,
+    "severity": 0,
+    "severity_value": 0,
+    "condition": "best_score > 2",
+    "message": "Method 'symsim' performs much better than controls for metric 'ks_statistic_morans_I'\n  Task: spatial_simulators\n  Method: symsim\n  Metric: ks_statistic_morans_I\n  Best score: 0.297772261057033\n  Percentage outside range: 0%\n"
+  }
+]
diff --git a/spatial_simulators/v0.0.1-rc1/results.json b/spatial_simulators/v0.0.1-rc1/results.json
new file mode 100644
index 0000000..2bb7503
--- /dev/null
+++ b/spatial_simulators/v0.0.1-rc1/results.json
@@ -0,0 +1,5128 @@
+[
+  {
+    "dataset_name": "brain",
+    "method_name": "negative_normal",
+    "paramset_name": null,
+    "paramset": null,
+    "succeeded": true,
+    "run_exit_code": [0, 0],
+    "run_duration_secs": [194, 112],
+    "run_cpu_pct": [99.8, 99.3],
+    "run_peak_memory_mb": [1844, 607],
+    "run_disk_read_mb": [137, 69],
+    "run_disk_write_mb": [23, 22],
+    "metric_names": ["clustering_ari", "clustering_nmi", "crosscor_cosine", "crosscor_mantel", "ctdeconvolute_jsd", "ctdeconvolute_rmse", "ks_statistic_L_stats", "ks_statistic_morans_I", "ks_statistic_nn_correlation"],
+    "metric_values": [0.0007, 0.002, 0.5019, 0.0029, 0.6845, 0.0887, 76.9399, -0.1078, 0.6755],
+    "metric_components": [
+      {
+        "component_name": "downstream",
+        "metric_names": ["clustering_ari", "clustering_nmi", "svg_recall", "svg_precision", "ctdeconvolute_rmse", "ctdeconvolute_jsd", "crosscor_mantel", "crosscor_cosine"],
+        "succeeded": true,
+        "run_exit_code": [0, 0],
+        "run_duration_secs": [2.3, 1213],
+        "run_cpu_pct": [149.7, 99.9],
+        "run_peak_memory_mb": [873, 2765],
+        "run_disk_read_mb": [21, 182],
+        "run_disk_write_mb": [1, 1]
+      },
+      {
+        "component_name": "ks_statistic_gene_cell",
+        "metric_names": ["ks_statistic_frac_zero_genes_zstat", "ks_statistic_frac_zero_cells_zstat", "ks_statistic_lib_size_cells_zstat", "ks_statistic_efflib_size_cells_zstat", "ks_statistic_tmm_cells_zstat", "ks_statistic_scaled_var_cells_zstat", "ks_statistic_scaled_mean_cells_zstat", "ks_statistic_lib_fraczero_cells_zstat", "ks_statistic_pearson_cells_zstat", "ks_statistic_scaled_var_genes_zstat", "ks_statistic_scaled_mean_genes_zstat", "ks_statistic_pearson_genes_zstat", "ks_statistic_mean_var_genes_zstat", "ks_statistic_mean_fraczero_genes_zstat", "ks_statistic_frac_zero_genes_tstat", "ks_statistic_frac_zero_cells_tstat", "ks_statistic_lib_size_cells_tstat", "ks_statistic_efflib_size_cells_tstat", "ks_statistic_tmm_cells_tstat", "ks_statistic_scaled_var_cells_tstat", "ks_statistic_scaled_mean_cells_tstat", "ks_statistic_lib_fraczero_cells_tstat", "ks_statistic_pearson_cells_tstat", "ks_statistic_scaled_var_genes_tstat", "ks_statistic_scaled_mean_genes_tstat", "ks_statistic_pearson_genes_tstat", "ks_statistic_mean_var_genes_tstat", "ks_statistic_mean_fraczero_genes_tstat"],
+        "succeeded": true,
+        "run_exit_code": [0, 0],
+        "run_duration_secs": [2.3, 217],
+        "run_cpu_pct": [148.3, 99.9],
+        "run_peak_memory_mb": [872, 1229],
+        "run_disk_read_mb": [21, 123],
+        "run_disk_write_mb": [1, 1]
+      },
+      {
+        "component_name": "ks_statistic_sc_features",
+        "metric_names": ["ks_statistic_L_stats", "ks_statistic_nn_correlation", "ks_statistic_morans_I"],
+        "succeeded": true,
+        "run_exit_code": [0, 0],
+        "run_duration_secs": [2.5, 3130],
+        "run_cpu_pct": [208.5, 100],
+        "run_peak_memory_mb": [1536, 18432],
+        "run_disk_read_mb": [21, 257],
+        "run_disk_write_mb": [1, 1]
+      }
+    ]
+  },
+  {
+    "dataset_name": "brain",
+    "method_name": "negative_shuffle",
+    "paramset_name": null,
+    "paramset": null,
+    "succeeded": true,
+    "run_exit_code": [0, 0],
+    "run_duration_secs": [192, 113],
+    "run_cpu_pct": [99.8, 99.9],
+    "run_peak_memory_mb": [1844, 625],
+    "run_disk_read_mb": [121, 69],
+    "run_disk_write_mb": [7, 7],
+    "metric_names": ["clustering_ari", "clustering_nmi", "crosscor_cosine", "crosscor_mantel", "ctdeconvolute_jsd", "ctdeconvolute_rmse", "ks_statistic_L_stats", "ks_statistic_morans_I", "ks_statistic_nn_correlation"],
+    "metric_values": [0.0001, 0.0011, 0.5007, 0.0005, 0.566, 0.0729, 24.6809, 0.348, 0.534],
+    "metric_components": [
+      {
+        "component_name": "downstream",
+        "metric_names": ["clustering_ari", "clustering_nmi", "svg_recall", "svg_precision", "ctdeconvolute_rmse", "ctdeconvolute_jsd", "crosscor_mantel", "crosscor_cosine"],
+        "succeeded": true,
+        "run_exit_code": [0, 0],
+        "run_duration_secs": [2.4, 899],
+        "run_cpu_pct": [140.8, 99.9],
+        "run_peak_memory_mb": [870, 2765],
+        "run_disk_read_mb": [21, 166],
+        "run_disk_write_mb": [1, 1]
+      },
+      {
+        "component_name": "ks_statistic_gene_cell",
+        "metric_names": ["ks_statistic_frac_zero_genes_zstat", "ks_statistic_frac_zero_cells_zstat", "ks_statistic_lib_size_cells_zstat", "ks_statistic_efflib_size_cells_zstat", "ks_statistic_tmm_cells_zstat", "ks_statistic_scaled_var_cells_zstat", "ks_statistic_scaled_mean_cells_zstat", "ks_statistic_lib_fraczero_cells_zstat", "ks_statistic_pearson_cells_zstat", "ks_statistic_scaled_var_genes_zstat", "ks_statistic_scaled_mean_genes_zstat", "ks_statistic_pearson_genes_zstat", "ks_statistic_mean_var_genes_zstat", "ks_statistic_mean_fraczero_genes_zstat", "ks_statistic_frac_zero_genes_tstat", "ks_statistic_frac_zero_cells_tstat", "ks_statistic_lib_size_cells_tstat", "ks_statistic_efflib_size_cells_tstat", "ks_statistic_tmm_cells_tstat", "ks_statistic_scaled_var_cells_tstat", "ks_statistic_scaled_mean_cells_tstat", "ks_statistic_lib_fraczero_cells_tstat", "ks_statistic_pearson_cells_tstat", "ks_statistic_scaled_var_genes_tstat", "ks_statistic_scaled_mean_genes_tstat", "ks_statistic_pearson_genes_tstat", "ks_statistic_mean_var_genes_tstat", "ks_statistic_mean_fraczero_genes_tstat"],
+        "succeeded": true,
+        "run_exit_code": [0, 0],
+        "run_duration_secs": [2.4, 179],
+        "run_cpu_pct": [203.2, 99.9],
+        "run_peak_memory_mb": [1536, 1332],
+        "run_disk_read_mb": [21, 108],
+        "run_disk_write_mb": [1, 1]
+      },
+      {
+        "component_name": "ks_statistic_sc_features",
+        "metric_names": ["ks_statistic_L_stats", "ks_statistic_nn_correlation", "ks_statistic_morans_I"],
+        "succeeded": true,
+        "run_exit_code": [0, 0],
+        "run_duration_secs": [2.4, 4944],
+        "run_cpu_pct": [203, 100],
+        "run_peak_memory_mb": [2868, 18842],
+        "run_disk_read_mb": [21, 241],
+        "run_disk_write_mb": [1, 1]
+      }
+    ]
+  },
+  {
+    "dataset_name": "brain",
+    "method_name": "positive",
+    "paramset_name": null,
+    "paramset": null,
+    "succeeded": true,
+    "run_exit_code": [0, 0],
+    "run_duration_secs": [208, 122],
+    "run_cpu_pct": [99.8, 99.3],
+    "run_peak_memory_mb": [1844, 524],
+    "run_disk_read_mb": [140, 70],
+    "run_disk_write_mb": [24, 24],
+    "metric_names": ["clustering_ari", "clustering_nmi", "crosscor_cosine", "crosscor_mantel", "ctdeconvolute_jsd", "ctdeconvolute_rmse", "ks_statistic_L_stats", "ks_statistic_morans_I", "ks_statistic_nn_correlation"],
+    "metric_values": [0.7207, 0.7236, 0.8937, 0.7938, 0, 0, -0.5645, -1.1827, -0.568],
+    "metric_components": [
+      {
+        "component_name": "downstream",
+        "metric_names": ["clustering_ari", "clustering_nmi", "svg_recall", "svg_precision", "ctdeconvolute_rmse", "ctdeconvolute_jsd", "crosscor_mantel", "crosscor_cosine"],
+        "succeeded": true,
+        "run_exit_code": [0, 0],
+        "run_duration_secs": [2.3, 1033],
+        "run_cpu_pct": [145.7, 99.9],
+        "run_peak_memory_mb": [871, 2663],
+        "run_disk_read_mb": [21, 184],
+        "run_disk_write_mb": [1, 1]
+      },
+      {
+        "component_name": "ks_statistic_gene_cell",
+        "metric_names": ["ks_statistic_frac_zero_genes_zstat", "ks_statistic_frac_zero_cells_zstat", "ks_statistic_lib_size_cells_zstat", "ks_statistic_efflib_size_cells_zstat", "ks_statistic_tmm_cells_zstat", "ks_statistic_scaled_var_cells_zstat", "ks_statistic_scaled_mean_cells_zstat", "ks_statistic_lib_fraczero_cells_zstat", "ks_statistic_pearson_cells_zstat", "ks_statistic_scaled_var_genes_zstat", "ks_statistic_scaled_mean_genes_zstat", "ks_statistic_pearson_genes_zstat", "ks_statistic_mean_var_genes_zstat", "ks_statistic_mean_fraczero_genes_zstat", "ks_statistic_frac_zero_genes_tstat", "ks_statistic_frac_zero_cells_tstat", "ks_statistic_lib_size_cells_tstat", "ks_statistic_efflib_size_cells_tstat", "ks_statistic_tmm_cells_tstat", "ks_statistic_scaled_var_cells_tstat", "ks_statistic_scaled_mean_cells_tstat", "ks_statistic_lib_fraczero_cells_tstat", "ks_statistic_pearson_cells_tstat", "ks_statistic_scaled_var_genes_tstat", "ks_statistic_scaled_mean_genes_tstat", "ks_statistic_pearson_genes_tstat", "ks_statistic_mean_var_genes_tstat", "ks_statistic_mean_fraczero_genes_tstat"],
+        "succeeded": true,
+        "run_exit_code": [0, 0],
+        "run_duration_secs": [2.3, 193],
+        "run_cpu_pct": [144.6, 99.9],
+        "run_peak_memory_mb": [871, 1229],
+        "run_disk_read_mb": [21, 126],
+        "run_disk_write_mb": [1, 1]
+      },
+      {
+        "component_name": "ks_statistic_sc_features",
+        "metric_names": ["ks_statistic_L_stats", "ks_statistic_nn_correlation", "ks_statistic_morans_I"],
+        "succeeded": true,
+        "run_exit_code": [0, 0],
+        "run_duration_secs": [2.4, 3434],
+        "run_cpu_pct": [179.1, 100],
+        "run_peak_memory_mb": [1536, 20890],
+        "run_disk_read_mb": [21, 259],
+        "run_disk_write_mb": [1, 1]
+      }
+    ]
+  },
+  {
+    "dataset_name": "brain",
+    "method_name": "scdesign2",
+    "paramset_name": null,
+    "paramset": null,
+    "succeeded": true,
+    "run_exit_code": [0, 0],
+    "run_duration_secs": [186, 557],
+    "run_cpu_pct": [99.8, 275],
+    "run_peak_memory_mb": [1844, 2868],
+    "run_disk_read_mb": [121, 79],
+    "run_disk_write_mb": [7, 15],
+    "metric_names": ["clustering_ari", "clustering_nmi", "crosscor_mantel", "ctdeconvolute_jsd", "ctdeconvolute_rmse", "ks_statistic_L_stats", "ks_statistic_morans_I", "ks_statistic_nn_correlation", "svg_precision"],
+    "metric_values": [0.0004, 0.001, -0.0717, 0.2696, 0.0544, 36.9075, 71.1324, 15.9558, 0],
+    "metric_components": [
+      {
+        "component_name": "downstream",
+        "metric_names": ["clustering_ari", "clustering_nmi", "svg_recall", "svg_precision", "ctdeconvolute_rmse", "ctdeconvolute_jsd", "crosscor_mantel", "crosscor_cosine"],
+        "succeeded": true,
+        "run_exit_code": [0, 0],
+        "run_duration_secs": [2.3, 994],
+        "run_cpu_pct": [225.3, 100],
+        "run_peak_memory_mb": [1536, 2765],
+        "run_disk_read_mb": [21, 166],
+        "run_disk_write_mb": [1, 1]
+      },
+      {
+        "component_name": "ks_statistic_gene_cell",
+        "metric_names": ["ks_statistic_frac_zero_genes_zstat", "ks_statistic_frac_zero_cells_zstat", "ks_statistic_lib_size_cells_zstat", "ks_statistic_efflib_size_cells_zstat", "ks_statistic_tmm_cells_zstat", "ks_statistic_scaled_var_cells_zstat", "ks_statistic_scaled_mean_cells_zstat", "ks_statistic_lib_fraczero_cells_zstat", "ks_statistic_pearson_cells_zstat", "ks_statistic_scaled_var_genes_zstat", "ks_statistic_scaled_mean_genes_zstat", "ks_statistic_pearson_genes_zstat", "ks_statistic_mean_var_genes_zstat", "ks_statistic_mean_fraczero_genes_zstat", "ks_statistic_frac_zero_genes_tstat", "ks_statistic_frac_zero_cells_tstat", "ks_statistic_lib_size_cells_tstat", "ks_statistic_efflib_size_cells_tstat", "ks_statistic_tmm_cells_tstat", "ks_statistic_scaled_var_cells_tstat", "ks_statistic_scaled_mean_cells_tstat", "ks_statistic_lib_fraczero_cells_tstat", "ks_statistic_pearson_cells_tstat", "ks_statistic_scaled_var_genes_tstat", "ks_statistic_scaled_mean_genes_tstat", "ks_statistic_pearson_genes_tstat", "ks_statistic_mean_var_genes_tstat", "ks_statistic_mean_fraczero_genes_tstat"],
+        "succeeded": true,
+        "run_exit_code": [0, 0],
+        "run_duration_secs": [2.3, 187],
+        "run_cpu_pct": [194.2, 99.9],
+        "run_peak_memory_mb": [1536, 1229],
+        "run_disk_read_mb": [21, 108],
+        "run_disk_write_mb": [1, 1]
+      },
+      {
+        "component_name": "ks_statistic_sc_features",
+        "metric_names": ["ks_statistic_L_stats", "ks_statistic_nn_correlation", "ks_statistic_morans_I"],
+        "succeeded": true,
+        "run_exit_code": [0, 0],
+        "run_duration_secs": [2.5, 3519],
+        "run_cpu_pct": [242.1, 100],
+        "run_peak_memory_mb": [2868, 24372],
+        "run_disk_read_mb": [21, 241],
+        "run_disk_write_mb": [1, 1]
+      }
+    ]
+  },
+  {
+    "dataset_name": "brain",
+    "method_name": "scdesign3_nb",
+    "paramset_name": null,
+    "paramset": null,
+    "succeeded": true,
+    "run_exit_code": [0, 0],
+    "run_duration_secs": [188, 9325],
+    "run_cpu_pct": [99.7, 100.1],
+    "run_peak_memory_mb": [1844, 8397],
+    "run_disk_read_mb": [121, 105],
+    "run_disk_write_mb": [7, 6],
+    "metric_names": ["clustering_ari", "clustering_nmi", "crosscor_mantel", "ctdeconvolute_jsd", "ctdeconvolute_rmse", "ks_statistic_L_stats", "ks_statistic_morans_I", "ks_statistic_nn_correlation", "svg_precision"],
+    "metric_values": [0.0009, 0.0019, 0.0691, 0.3127, 0.0625, 31.805, 6.0248, -0.1692, 0],
+    "metric_components": [
+      {
+        "component_name": "downstream",
+        "metric_names": ["clustering_ari", "clustering_nmi", "svg_recall", "svg_precision", "ctdeconvolute_rmse", "ctdeconvolute_jsd", "crosscor_mantel", "crosscor_cosine"],
+        "succeeded": true,
+        "run_exit_code": [0, 0],
+        "run_duration_secs": [2.4, 1012],
+        "run_cpu_pct": [257.4, 99.9],
+        "run_peak_memory_mb": [2868, 2560],
+        "run_disk_read_mb": [21, 166],
+        "run_disk_write_mb": [1, 1]
+      },
+      {
+        "component_name": "ks_statistic_gene_cell",
+        "metric_names": ["ks_statistic_frac_zero_genes_zstat", "ks_statistic_frac_zero_cells_zstat", "ks_statistic_lib_size_cells_zstat", "ks_statistic_efflib_size_cells_zstat", "ks_statistic_tmm_cells_zstat", "ks_statistic_scaled_var_cells_zstat", "ks_statistic_scaled_mean_cells_zstat", "ks_statistic_lib_fraczero_cells_zstat", "ks_statistic_pearson_cells_zstat", "ks_statistic_scaled_var_genes_zstat", "ks_statistic_scaled_mean_genes_zstat", "ks_statistic_pearson_genes_zstat", "ks_statistic_mean_var_genes_zstat", "ks_statistic_mean_fraczero_genes_zstat", "ks_statistic_frac_zero_genes_tstat", "ks_statistic_frac_zero_cells_tstat", "ks_statistic_lib_size_cells_tstat", "ks_statistic_efflib_size_cells_tstat", "ks_statistic_tmm_cells_tstat", "ks_statistic_scaled_var_cells_tstat", "ks_statistic_scaled_mean_cells_tstat", "ks_statistic_lib_fraczero_cells_tstat", "ks_statistic_pearson_cells_tstat", "ks_statistic_scaled_var_genes_tstat", "ks_statistic_scaled_mean_genes_tstat", "ks_statistic_pearson_genes_tstat", "ks_statistic_mean_var_genes_tstat", "ks_statistic_mean_fraczero_genes_tstat"],
+        "succeeded": true,
+        "run_exit_code": [0, 0],
+        "run_duration_secs": [2.5, 187],
+        "run_cpu_pct": [312.7, 100],
+        "run_peak_memory_mb": [2868, 1127],
+        "run_disk_read_mb": [21, 108],
+        "run_disk_write_mb": [1, 1]
+      },
+      {
+        "component_name": "ks_statistic_sc_features",
+        "metric_names": ["ks_statistic_L_stats", "ks_statistic_nn_correlation", "ks_statistic_morans_I"],
+        "succeeded": true,
+        "run_exit_code": [0, 0],
+        "run_duration_secs": [2.4, 3471],
+        "run_cpu_pct": [340.2, 100],
+        "run_peak_memory_mb": [2868, 20378],
+        "run_disk_read_mb": [21, 241],
+        "run_disk_write_mb": [1, 1]
+      }
+    ]
+  },
+  {
+    "dataset_name": "brain",
+    "method_name": "scdesign3_poisson",
+    "paramset_name": null,
+    "paramset": null,
+    "succeeded": true,
+    "run_exit_code": [0, 0],
+    "run_duration_secs": [189, 16071],
+    "run_cpu_pct": [99.7, 100.1],
+    "run_peak_memory_mb": [1741, 8602],
+    "run_disk_read_mb": [121, 105],
+    "run_disk_write_mb": [7, 6],
+    "metric_names": ["clustering_ari", "clustering_nmi", "crosscor_cosine", "crosscor_mantel", "ctdeconvolute_jsd", "ctdeconvolute_rmse", "ks_statistic_L_stats", "ks_statistic_morans_I", "ks_statistic_nn_correlation", "svg_precision"],
+    "metric_values": [0.001, 0.0026, 0.5749, 0.1603, 0.2651, 0.0586, 47.3705, 73.7869, 28.9802, 0],
+    "metric_components": [
+      {
+        "component_name": "downstream",
+        "metric_names": ["clustering_ari", "clustering_nmi", "svg_recall", "svg_precision", "ctdeconvolute_rmse", "ctdeconvolute_jsd", "crosscor_mantel", "crosscor_cosine"],
+        "succeeded": true,
+        "run_exit_code": [0, 0],
+        "run_duration_secs": [2.4, 988],
+        "run_cpu_pct": [343.2, 99.9],
+        "run_peak_memory_mb": [2868, 2970],
+        "run_disk_read_mb": [21, 166],
+        "run_disk_write_mb": [1, 1]
+      },
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+]
diff --git a/spatial_simulators/v0.0.1-rc1/task_info.json b/spatial_simulators/v0.0.1-rc1/task_info.json
new file mode 100644
index 0000000..24cbd9b
--- /dev/null
+++ b/spatial_simulators/v0.0.1-rc1/task_info.json
@@ -0,0 +1,66 @@
+{
+    "name": "spatial_simulators",
+    "commit": "3d78c563c640709eee81833b9cf0e19ad31549c6",
+    "label": "Spatial Simulators",
+    "summary": "Assessing the quality of spatial transcriptomics simulators",
+    "description": "Computational methods for spatially resolved transcriptomics (SRT) are frequently developed \nand assessed through data simulation. The effectiveness of these evaluations relies on the \nsimulation methods' ability to accurately reflect experimental data. However, a systematic \nevaluation framework for spatial simulators is lacking. Here, we present SpatialSimBench, \na comprehensive evaluation framework that assesses 13 simulation methods using 10 distinct \nSTR datasets.\n\nThe research goal of this benchmark is to systematically evaluate and compare the\nperformance of various simulation methods for spatial transcriptomics (ST) data.\nIt aims to address the lack of a comprehensive evaluation framework for spatial simulators\nand explore the feasibility of leveraging existing single-cell simulators for ST data.\nThe experimental setup involves collecting public spatial transcriptomics datasets and\ncorresponding scRNA-seq datasets.\nThe spatial and scRNA-seq datasets can originate from different study but should consist\nof similar cell types from similar tissues.",
+    "repository": "https://github.com/openproblems-bio/task_spatial_simulators",
+    "authors": [
+        {
+        "name": "Xiaoqi Liang",
+        "roles": [
+            "author"
+        ],
+        "github": "littlecabiria",
+        "orcid": "0009-0004-9625-1441",
+        "info": {}
+        },
+        {
+        "name": "Yue Cao",
+        "roles": [
+            "author",
+            "maintainer"
+        ],
+        "github": "ycao6928",
+        "orcid": "0000-0002-2356-4031",
+        "info": {}
+        },
+        {
+        "name": "Jean Yang",
+        "roles": [
+            "author"
+        ],
+        "github": "jeany21",
+        "orcid": "0000-0002-5271-2603",
+        "info": {}
+        },
+        {
+        "name": "Robrecht Cannoodt",
+        "roles": [
+            "contributor"
+        ],
+        "github": "rcannood",
+        "orcid": "0000-0003-3641-729X",
+        "info": {}
+        },
+        {
+        "name": "Sai Nirmayi Yasa",
+        "roles": [
+            "contributor"
+        ],
+        "github": "sainirmayi",
+        "orcid": "0009-0003-6319-9803",
+        "info": {}
+        }
+    ],
+    "license": "MIT",
+    "references": {
+        "doi": [
+        "10.1101/2024.05.29.596418"
+        ],
+        "bibtex": []
+    },
+    "version": "v0.0.1-rc1",
+    "is_prerelease": true,
+    "timestamp": "2026-06-23T13:12:37Z"
+}
\ No newline at end of file