{"id":"W3200458611","doi":"10.1016/j.jcin.2021.08.002","title":"Trust in Machine Learning Models for Mortality Prediction Following Mitral TEER","year":2021,"lang":"en","type":"letter","venue":"JACC: Cardiovascular Interventions","topic":"Cardiac Valve Diseases and Treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Montreal Heart Institute","funders":"","keywords":"Cardiology; Internal medicine; Computer science; Artificial intelligence; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","metaepi_broad"],"consensus_categories":[],"category_scores_codex":[0.000608175,0.0004971645,0.001581869,0.0003763536,0.0001642434,0.0001021458,0.0001279729,0.0006372853,0.0001334998],"category_scores_gemma":[0.0001891415,0.0005068295,0.06582048,0.0003098565,0.00003426645,0.0001921237,0.0001040998,0.001369098,0.00001478622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004939043,"about_ca_system_score_gemma":0.0001455247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006218489,"about_ca_topic_score_gemma":0.00003189983,"domain_scores_codex":[0.9965482,0.0003276847,0.0008060022,0.0009326085,0.0008227613,0.0005627685],"domain_scores_gemma":[0.9984334,0.00006553145,0.0001423097,0.001016888,0.0002091716,0.0001327386],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"meta_analysis","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002031773,0.001776576,0.3358494,0.009903529,0.3879249,0.006614446,0.0002640926,0.01725829,0.000008591095,0.00005752152,0.2301026,0.01003679],"study_design_scores_gemma":[0.02269343,0.0007202076,0.2466602,0.01047486,0.1870809,0.0003418265,0.0003508565,0.01134439,0.00003033805,0.0008021441,0.5176193,0.001881513],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.2418656,0.5196995,0.1070531,0.06204899,0.01745261,0.02180913,0.01468373,0.001677827,0.01370941],"genre_scores_gemma":[0.8812522,0.00144463,0.001579168,0.0225482,0.007146151,0.004809583,0.06670094,0.0006158925,0.01390322],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6393866,"threshold_uncertainty_score":0.9997383,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07369277606342145,"score_gpt":0.3490643699852587,"score_spread":0.2753715939218372,"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."}}