{"id":"W3022369650","doi":"10.1016/j.ccell.2020.04.012","title":"Comprehensive Analysis of Genetic Ancestry and Its Molecular Correlates in Cancer","year":2020,"lang":"en","type":"article","venue":"Cancer Cell","topic":"Epigenetics and DNA Methylation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":327,"is_retracted":false,"has_abstract":false,"ca_institutions":"BC Cancer Agency","funders":"National Institute of Environmental Health Sciences; National Cancer Institute; Bayer Fund; Bayer Corporation; AstraZeneca; Eli Lilly and Company","keywords":"Cancer; Biology; Genetics; DNA methylation; Confounding; Gene; Bladder cancer; Kidney cancer; Genome; Cancer research; Medicine; Internal medicine; Gene expression","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002008861,0.00009695975,0.0001864043,0.00003260143,0.00001281037,0.000005415604,0.00007433814,0.0000867366,0.00004793202],"category_scores_gemma":[0.000007716642,0.0001012857,0.00005563148,0.000251244,0.00002926604,0.000002058481,0.00004829388,0.00004839724,5.138613e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001079238,"about_ca_system_score_gemma":0.00004685031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001731173,"about_ca_topic_score_gemma":0.0001419357,"domain_scores_codex":[0.9993466,0.00002965616,0.0001770071,0.0002605676,0.00007026277,0.0001158895],"domain_scores_gemma":[0.9996626,0.000007853944,0.00008685579,0.0001008283,0.00007360112,0.00006823678],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000231569,0.00001360636,0.09758937,0.00005579419,0.0001123697,0.000002270696,0.0001232946,0.03387642,0.8669617,0.000004325329,0.00001460552,0.001223047],"study_design_scores_gemma":[0.0004075805,0.0001083924,0.1031258,0.00001154319,0.0002412043,7.858204e-8,0.00006981302,0.0111474,0.8827225,0.00001293762,0.001992224,0.0001605118],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8708637,0.1284063,0.0002997476,0.00007619249,0.00004152822,0.00008489816,0.00003918984,0.000002253807,0.0001862296],"genre_scores_gemma":[0.9811651,0.01835661,0.0001286065,0.0002295545,0.00003839337,0.00001830325,0.00002753841,0.00001063355,0.0000253386],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1103013,"threshold_uncertainty_score":0.4130309,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02839786868800517,"score_gpt":0.2941881195969248,"score_spread":0.2657902509089197,"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."}}