{"id":"W3004570628","doi":"10.1038/s41467-019-13929-1","title":"Combined burden and functional impact tests for cancer driver discovery using DriverPower","year":2020,"lang":"en","type":"article","venue":"Nature Communications","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":66,"is_retracted":false,"has_abstract":true,"ca_institutions":"Prostate Cancer Canada; Genome Canada; Institute of Cancer Research; Princess Margaret Cancer Centre; Mount Sinai Hospital; Lunenfeld-Tanenbaum Research Institute; University of Calgary; Vector Institute; Canada's Michael Smith Genome Sciences Centre; University Health Network; McGill University and Génome Québec Innovation Centre; Toronto General Hospital; University of Toronto; BC Cancer Agency; SickKids Foundation; University of Ottawa; McGill University; Simon Fraser University; Ontario Institute for Cancer Research","funders":"National Cancer Institute; National Institute of Environmental Health Sciences; Government of Ontario; Francis Crick Institute","keywords":"Cancer; Computer science; Computational biology; Medicine; Bioinformatics; Biology; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.04750407,0.001559226,0.002276891,0.005451051,0.0009840179,0.002428882,0.002378446,0.001512599,0.01151163],"category_scores_gemma":[0.1656437,0.0009262366,0.005223115,0.004085446,0.001267898,0.001881869,0.003051294,0.003141744,0.001834256],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007740983,"about_ca_system_score_gemma":0.003216625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002183096,"about_ca_topic_score_gemma":0.003101654,"domain_scores_codex":[0.9673622,0.02470822,0.001562952,0.002487405,0.003279066,0.0006001993],"domain_scores_gemma":[0.8306057,0.1554434,0.003585647,0.007420542,0.001799199,0.001145471],"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":[0.007684781,0.0006665501,0.2815942,0.002475442,0.02755247,0.002013481,0.0008653731,0.1291494,0.005846828,0.02805625,0.06287101,0.4512242],"study_design_scores_gemma":[0.002319192,0.002251759,0.04262075,0.000346778,0.005900061,0.002197118,0.0002683189,0.7825315,0.008368884,0.1136414,0.03931984,0.0002343765],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.09833357,0.003069932,0.8618391,0.002984802,0.0004973513,0.0009603617,0.01476312,0.01318299,0.004368733],"genre_scores_gemma":[0.7135651,0.0008598639,0.2627819,0.001575059,0.0005194126,0.002778057,0.01205592,0.00305677,0.00280796],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04750407,"threshold_uncertainty_score":0.2512285,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5251382102481553,"score_gpt":0.5807650512924323,"score_spread":0.05562684104427695,"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."}}