{"id":"W2776882820","doi":"10.1158/0008-5472.can-17-1345","title":"ConsensusDriver Improves upon Individual Algorithms for Predicting Driver Alterations in Different Cancer Types and Individual Patients","year":2017,"lang":"en","type":"article","venue":"Cancer Research","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Cancer Agency","funders":"","keywords":"Cancer; Algorithm; Computer science; Computational biology; Medicine; Biology; Internal medicine","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":[0.005839069,0.001314148,0.001487119,0.002868465,0.0005622837,0.001492972,0.001693795,0.001368313,0.003017828],"category_scores_gemma":[0.01361708,0.0005440911,0.001750441,0.001048939,0.0002946687,0.001180636,0.001457857,0.001572366,0.001438822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005803323,"about_ca_system_score_gemma":0.001602267,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003594248,"about_ca_topic_score_gemma":0.005825823,"domain_scores_codex":[0.997327,0.0006991204,0.0002220985,0.00101749,0.0005799333,0.00015432],"domain_scores_gemma":[0.9929972,0.004231369,0.0005767916,0.0008381901,0.001128181,0.0002281487],"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":[0.001472428,0.0004337031,0.1333605,0.0005328978,0.001781679,0.0003828634,0.0001598783,0.2136309,0.01486115,0.002024981,0.01892099,0.6124379],"study_design_scores_gemma":[0.0001721454,0.0003414283,0.01118528,0.00006641064,0.000289604,0.0005175764,0.00006826293,0.9650536,0.0136716,0.004035083,0.004529946,0.00006916191],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3057023,0.003582308,0.6624819,0.001224929,0.0003036077,0.0004271228,0.003946332,0.01743741,0.004894076],"genre_scores_gemma":[0.6873582,0.0005068239,0.3018466,0.0005670293,0.0001318572,0.0002391523,0.006257831,0.0008753365,0.002217222],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005839069,"threshold_uncertainty_score":0.03088027,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6910529857859166,"score_gpt":0.6218502542468978,"score_spread":0.06920273153901879,"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."}}