{"id":"W2151684398","doi":"10.1371/journal.pcbi.1004147","title":"Protein Domain-Level Landscape of Cancer-Type-Specific Somatic Mutations","year":2015,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":81,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research; Lunenfeld-Tanenbaum Research Institute; University of Toronto","funders":"National Institutes of Health; National Human Genome Research Institute; Canada Excellence Research Chairs, Government of Canada; Avon Foundation for Women","keywords":"Biology; Genetics; Cancer; Mutation; Germline mutation; Protein kinase domain; Protein domain; Context (archaeology); Somatic cell; Computational biology; Suppressor; Cancer research; Gene; Mutant","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":[0.0007976742,0.0002323071,0.0005679823,0.0009688146,0.0002927291,0.0007362893,0.0003174734,0.000355704,0.0008258593],"category_scores_gemma":[0.002253846,0.0001960867,0.0004698015,0.001100594,0.0004176951,0.0005504065,0.0005366154,0.0003074856,0.0001207634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004992245,"about_ca_system_score_gemma":0.0003682539,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00133836,"about_ca_topic_score_gemma":0.00246031,"domain_scores_codex":[0.9996639,0.00008396004,0.00002133284,0.0001222329,0.00005585903,0.00005258572],"domain_scores_gemma":[0.9993439,0.0003680188,0.00009705862,0.00006631035,0.00007741088,0.00004725633],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008027164,0.000137481,0.3980962,0.000595679,0.0009773702,0.0006383044,0.0003915244,0.3009783,0.25444,0.005605448,0.0008699022,0.03646709],"study_design_scores_gemma":[0.00004095535,0.0002521731,0.3364409,0.00002585891,0.0004673693,0.0008409796,0.0004571978,0.6145127,0.03141534,0.01265211,0.002829713,0.00006478735],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935087,0.0002858976,0.005213373,0.00004512845,0.000001597174,0.000006922138,0.0004451034,0.00006765873,0.0004257101],"genre_scores_gemma":[0.995455,0.0001362203,0.003124908,0.0000234315,0.00000179256,0.0000112823,0.001108643,0.00002870606,0.0001100565],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00133836,"threshold_uncertainty_score":0.004218578,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04210770789835727,"score_gpt":0.2813313158220109,"score_spread":0.2392236079236537,"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."}}