{"id":"W2012673284","doi":"10.1038/nmeth.2562","title":"Computational approaches to identify functional genetic variants in cancer genomes","year":2013,"lang":"en","type":"article","venue":"Nature Methods","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":178,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ontario Institute for Cancer Research; University of Toronto","funders":"National Cancer Institute; National Human Genome Research Institute; Wellcome Trust","keywords":"Genome; Somatic cell; Carcinogenesis; Biology; Computational biology; Cancer; Genetics; Cancer genome sequencing; Phenotype; Mutation; Genomics; 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":[0.001719082,0.0006674245,0.000781489,0.002349434,0.0008303935,0.00142229,0.001763919,0.001005329,0.002549286],"category_scores_gemma":[0.008889994,0.0007222835,0.001819304,0.001541307,0.0007792406,0.001016559,0.001216893,0.001209174,0.0002608049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009774184,"about_ca_system_score_gemma":0.001287301,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00534058,"about_ca_topic_score_gemma":0.008697107,"domain_scores_codex":[0.999458,0.0002626715,0.00003160584,0.00009737186,0.0001115327,0.00003887202],"domain_scores_gemma":[0.9954665,0.004056897,0.0001219257,0.0001849233,0.0001098064,0.00005998631],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003356895,0.0002055678,0.009080214,0.0003014527,0.0005385043,0.0002868171,0.0001093252,0.8963035,0.002227262,0.04275049,0.0017017,0.04615948],"study_design_scores_gemma":[0.00003258616,0.00001180155,0.000397513,0.000008758736,0.00005775862,0.00003340566,0.00002208385,0.9751107,0.0004360043,0.02339111,0.0004931768,0.000005221329],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2505743,0.001374981,0.7335853,0.001758698,0.0001346801,0.0002458744,0.003467019,0.003130227,0.005728921],"genre_scores_gemma":[0.7310235,0.0006741047,0.2634906,0.0003755738,0.00007949961,0.0003412969,0.002837032,0.0002300801,0.0009483355],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00534058,"threshold_uncertainty_score":0.01061898,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05485723337070874,"score_gpt":0.3627371022946355,"score_spread":0.3078798689239268,"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."}}