{"id":"W4295876072","doi":"10.1093/bib/bbac381","title":"TSomVar: a tumor-only somatic and germline variant identification method with random forest","year":2022,"lang":"en","type":"article","venue":"Briefings in Bioinformatics","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Chinese Academy of Sciences; National Natural Science Foundation of China","keywords":"Somatic cell; Germline; Computational biology; Biology; Annotation; Germline mutation; Identification (biology); Genetics; Gene; Mutation","routes":{"ca_aff":true,"ca_fund":false,"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":[0.003681045,0.001733398,0.001293451,0.002611342,0.0008959378,0.001131506,0.002026955,0.00165913,0.003710625],"category_scores_gemma":[0.006284593,0.0008571461,0.00277856,0.001587,0.0004141215,0.001261825,0.001210801,0.002086358,0.002588353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004119906,"about_ca_system_score_gemma":0.001815358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005029413,"about_ca_topic_score_gemma":0.009999839,"domain_scores_codex":[0.9979575,0.0005710753,0.0001707769,0.0006944529,0.0004044333,0.0002017035],"domain_scores_gemma":[0.9981638,0.001091533,0.0001323813,0.0002115253,0.0003177777,0.00008291497],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00101901,0.0004637841,0.0233862,0.0008329924,0.001273405,0.0008035083,0.0002632689,0.1147414,0.02161078,0.004329832,0.05886062,0.7724152],"study_design_scores_gemma":[0.0002277332,0.0001744929,0.003567327,0.00006815745,0.0002184581,0.0005306304,0.00005462109,0.9632683,0.007936988,0.008404936,0.01546013,0.00008810712],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0254975,0.001159057,0.9397034,0.0003346392,0.0003060037,0.000315086,0.004018408,0.02762831,0.00103759],"genre_scores_gemma":[0.1536671,0.0005647818,0.8147303,0.000582835,0.0002409832,0.0007770541,0.0235968,0.002800519,0.003039745],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005029413,"threshold_uncertainty_score":0.01946747,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004826215305935705,"score_gpt":0.2263687725438884,"score_spread":0.2215425572379527,"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."}}