{"id":"W4206904962","doi":"10.1101/2022.01.23.477261","title":"Regional Mutational Signature Activities in Cancer Genomes","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Vector Institute","funders":"National Cancer Institute; National Institutes of Health; Canadian Institute for Advanced Research","keywords":"Genome; Biology; Genetics; Computational biology; Chromatin; Context (archaeology); Genomics; Mutation; Mutation Accumulation; Evolutionary biology; Gene","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":[0.0008260998,0.0003738476,0.0005360142,0.002569644,0.0004032808,0.000787356,0.0004292461,0.0004605159,0.001670754],"category_scores_gemma":[0.003970701,0.0003427838,0.001229284,0.00439016,0.0002680485,0.0005406674,0.001059977,0.000597116,0.0005998145],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004902103,"about_ca_system_score_gemma":0.0004105481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002899114,"about_ca_topic_score_gemma":0.004434331,"domain_scores_codex":[0.999176,0.0001459484,0.00005455528,0.000421352,0.0001266302,0.00007556588],"domain_scores_gemma":[0.9988031,0.0004410186,0.0002790068,0.0002294428,0.0001624134,0.00008499696],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001841454,0.0001381788,0.455206,0.001128298,0.001343415,0.0007857963,0.002005008,0.09373428,0.2628776,0.007612524,0.008092454,0.165235],"study_design_scores_gemma":[0.00007055086,0.0004738772,0.7481136,0.00008077842,0.0004574507,0.002091714,0.0007478653,0.15786,0.05011233,0.01169985,0.02815772,0.0001341712],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8925769,0.00073459,0.07291931,0.00009521176,0.00001444446,0.00008626878,0.02825399,0.003222765,0.00209646],"genre_scores_gemma":[0.8499184,0.0003212435,0.1025465,0.00007095138,0.000009578547,0.0001553176,0.04559209,0.0006952159,0.0006905854],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002899114,"threshold_uncertainty_score":0.005764484,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0126064061341717,"score_gpt":0.2388305456509592,"score_spread":0.2262241395167875,"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."}}