{"id":"W4282944250","doi":"10.1158/1538-7445.am2022-5046","title":"Abstract 5046: DeepTumour: Identify tumor origin from whole genome sequences","year":2022,"lang":"en","type":"article","venue":"Cancer Research","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Institute for Cancer Research","funders":"","keywords":"Chromatin; Genome; Biology; Mutation; Genetics; Mutation rate; Epigenetics; Cancer; Lineage (genetic); Mutation Accumulation; DNA; Computational biology; Gene","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":[0.001316564,0.001329871,0.00103341,0.002477279,0.0006635847,0.00161312,0.001379594,0.001440168,0.01145688],"category_scores_gemma":[0.004699172,0.0008942288,0.00149213,0.001458369,0.0005046853,0.001069856,0.001789184,0.001079297,0.007051565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005182551,"about_ca_system_score_gemma":0.0009233262,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002482666,"about_ca_topic_score_gemma":0.004093315,"domain_scores_codex":[0.9994726,0.00007960345,0.00002997202,0.0002291689,0.0001219027,0.00006679315],"domain_scores_gemma":[0.999009,0.0004212865,0.0001298351,0.0002134052,0.0001436997,0.00008271875],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003798289,0.0004595902,0.08709652,0.002182067,0.001199611,0.002238258,0.0006754057,0.05535783,0.1037916,0.01157878,0.1527518,0.5788702],"study_design_scores_gemma":[0.0007451171,0.0007689588,0.03393294,0.0002756484,0.0004729333,0.002982971,0.0003633115,0.7063699,0.07586782,0.04399271,0.1340297,0.0001979528],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1732796,0.003275418,0.61289,0.001438939,0.000457247,0.0007169076,0.08394443,0.1146277,0.009369832],"genre_scores_gemma":[0.2947784,0.001199539,0.5437588,0.0007378637,0.0002014162,0.0008375433,0.1411008,0.007919856,0.009465695],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01145688,"threshold_uncertainty_score":0.0383271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05862259529043245,"score_gpt":0.3844026458100732,"score_spread":0.3257800505196407,"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."}}