{"id":"W3124990536","doi":"10.2139/ssrn.3582701","title":"Characterizing Genetic Intra-Tumor Heterogeneity Across 2,658 Human Cancer Genomes","year":2020,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Amgen (Canada); Simon Fraser University; Ontario Institute for Cancer Research; University of Toronto","funders":"Medical Research Council","keywords":"Cancer; Biology; Genome; Evolutionary biology; Computational biology; Tumor heterogeneity; Human genome; Genetics; 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":[0.0003633889,0.0001538277,0.0002705756,0.001008624,0.0003365849,0.0003866181,0.0001613157,0.000334711,0.001773043],"category_scores_gemma":[0.001247818,0.0001794681,0.0003671019,0.001283343,0.000229575,0.0001316524,0.0004177538,0.0003023634,0.0002887278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002563318,"about_ca_system_score_gemma":0.0002411176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002311666,"about_ca_topic_score_gemma":0.005844963,"domain_scores_codex":[0.9996284,0.00005125623,0.0000176384,0.0001750763,0.00007467886,0.00005292859],"domain_scores_gemma":[0.9993548,0.0003601567,0.000114507,0.00008564154,0.00003604108,0.00004884047],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001891981,0.0001008012,0.549594,0.0003100626,0.001348967,0.001008243,0.001030943,0.007841339,0.3680508,0.001680157,0.001645295,0.06549738],"study_design_scores_gemma":[0.00005855997,0.0001717902,0.9585759,0.00002497541,0.0004976136,0.001567029,0.0002163022,0.005629939,0.02346197,0.00132885,0.008445866,0.00002105217],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952387,0.0003452991,0.001250262,0.00003676239,0.000003581944,0.00000562678,0.002332918,0.0000460049,0.000740908],"genre_scores_gemma":[0.9941573,0.000171202,0.001223887,0.00004316674,0.000004553005,0.00000680843,0.003917238,0.00003326921,0.0004426867],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002311666,"threshold_uncertainty_score":0.005931377,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0116983426573916,"score_gpt":0.2742919060787158,"score_spread":0.2625935634213242,"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."}}