{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006565524,0.000352336,0.001001717,0.0004229187,0.0005613551,0.001688586,0.0007239125,0.005170083,0.002375101],"category_scores_gemma":[0.1054984,0.0003170224,0.0006979766,0.0003339865,0.0008267239,0.002548002,0.0006904082,0.008045535,0.001179069],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001695739,"about_ca_system_score_gemma":0.0008722944,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004053988,"about_ca_topic_score_gemma":0.005055952,"domain_scores_codex":[0.9966921,0.00231075,0.0002215118,0.0002131423,0.0003917886,0.0001708356],"domain_scores_gemma":[0.8962866,0.0955515,0.001875077,0.001601526,0.003593315,0.001091979],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00376025,0.0005840001,0.1119122,0.0005249709,0.0006983626,0.005609227,0.0007157287,0.05063983,0.0009097653,0.02590981,0.486349,0.3123868],"study_design_scores_gemma":[0.0005760497,0.000724541,0.01394004,0.0005659751,0.0002531936,0.002989777,0.0004774732,0.7190464,0.00141742,0.2148604,0.04502773,0.0001210421],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.05026008,0.003719032,0.02248109,0.9089914,0.006437635,0.00003796832,0.0006012026,0.0002033204,0.007268394],"genre_scores_gemma":[0.8886985,0.003402941,0.01008107,0.06653278,0.02294102,0.0001051606,0.0004108316,0.00010219,0.007725509],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.006565524,"threshold_uncertainty_score":0.03472221,"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."}}