{"id":"W2346103650","doi":"10.1016/j.ccell.2016.03.025","title":"Integrated Genomics for Pinpointing Survival Loci within Arm-Level Somatic Copy Number Alterations","year":2016,"lang":"en","type":"article","venue":"Cancer Cell","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":59,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Institute of General Medical Sciences; Canadian Institutes of Health Research; Geoffrey Beene Foundation; National Cancer Institute; National Institutes of Health; Memorial Sloan-Kettering Cancer Center; Goddard Space Flight Center; Sontag Foundation","keywords":"Somatic cell; Genomics; Biology; Copy-number variation; Genetics; Computational biology; Genome; Gene","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004131447,0.0004294685,0.0004677405,0.001115136,0.000302987,0.0007006083,0.0004827032,0.0005817616,0.002871628],"category_scores_gemma":[0.0003870029,0.0003282802,0.0005174675,0.000689553,0.0003066901,0.0003500273,0.0007071351,0.00105401,0.0004898237],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009056324,"about_ca_system_score_gemma":0.0004294632,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001722298,"about_ca_topic_score_gemma":0.004426831,"domain_scores_codex":[0.9996474,0.00003757568,0.00001144995,0.0001078209,0.0001365861,0.00005916402],"domain_scores_gemma":[0.9997943,0.00006779477,0.00005084028,0.00003213883,0.00002352453,0.00003136418],"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":[0.0001252709,0.00003271543,0.00146735,0.0000304425,0.00002587343,0.00005965448,0.00002103785,0.0007738661,0.9861436,0.0008109165,0.0001763482,0.01033287],"study_design_scores_gemma":[0.00006986182,0.0003954591,0.03893103,0.00001631867,0.0001966915,0.0006988498,0.0000684683,0.0148744,0.9331489,0.002715182,0.008858852,0.0000260619],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8490974,0.002185296,0.1314861,0.0007530171,0.00009677981,0.0001941024,0.005769191,0.002683493,0.007734651],"genre_scores_gemma":[0.9075994,0.0007916681,0.08200067,0.0003068691,0.0000412972,0.0001219784,0.003671063,0.0002171438,0.005249874],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002871628,"threshold_uncertainty_score":0.00960654,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02437089183439995,"score_gpt":0.2715564589107204,"score_spread":0.2471855670763204,"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."}}