{"id":"W3097094145","doi":"10.1101/2020.10.31.362988","title":"TMExplorer: A Tumour Microenvironment Single-cell RNAseq Database and Search Tool","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children; Children’s Health Research Institute; Ontario Institute for Cancer Research; London Health Sciences Centre; Western University","funders":"Lawson Health Research Institute","keywords":"Metadata; Computer science; Cancer; Database; Cancer-Associated Fibroblasts; Identification (biology); Tumor microenvironment; Computational biology; Biology; World Wide Web","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005347867,0.00342342,0.00371582,0.005182805,0.001374322,0.003835702,0.005926264,0.002195219,0.03637625],"category_scores_gemma":[0.01018224,0.002332011,0.003069161,0.005500793,0.0007150754,0.002416766,0.004088446,0.002458246,0.0362071],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001039713,"about_ca_system_score_gemma":0.003636958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002397243,"about_ca_topic_score_gemma":0.003901453,"domain_scores_codex":[0.996912,0.0006171096,0.0005133564,0.00100299,0.000710326,0.0002442135],"domain_scores_gemma":[0.9967793,0.001667836,0.0004202047,0.000542254,0.0003828362,0.0002076159],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002013857,0.0001341279,0.005299734,0.01190157,0.001431122,0.001172779,0.0008790574,0.005999246,0.04269996,0.008207994,0.8508065,0.06945414],"study_design_scores_gemma":[0.00150935,0.000446988,0.009313773,0.001220315,0.0009414887,0.002165207,0.0005352185,0.05201815,0.07259969,0.02239293,0.8362292,0.0006277259],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.005114098,0.002273648,0.1243774,0.0004743848,0.0003039394,0.000488895,0.4815653,0.3809231,0.004479211],"genre_scores_gemma":[0.02086196,0.001289331,0.2336678,0.00095317,0.00008899908,0.003160856,0.6821066,0.05397496,0.003896379],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.03637625,"threshold_uncertainty_score":0.1216906,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02276513883292388,"score_gpt":0.2067850355630695,"score_spread":0.1840198967301457,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}