{"id":"W4295775527","doi":"10.1016/j.jcmg.2022.07.002","title":"CAD-RADS™ 2.0 – 2022 Coronary Artery Disease-Reporting and Data System","year":2022,"lang":"en","type":"article","venue":"JACC. Cardiovascular imaging","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":140,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"British Heart Foundation","keywords":"Medicine; Coronary artery disease; CAD; Stenosis; Fractional flow reserve; Radiology; Internal medicine; Cardiology; Angiography; Coronary angiography; Myocardial infarction","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":[0.005841567,0.0008671424,0.001600784,0.00457067,0.0006759492,0.004316883,0.002131792,0.001982442,0.1706246],"category_scores_gemma":[0.02304356,0.0008427937,0.001048687,0.003737186,0.0004688438,0.001754773,0.002011876,0.002294272,0.1642385],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001620236,"about_ca_system_score_gemma":0.00451798,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007142149,"about_ca_topic_score_gemma":0.00537617,"domain_scores_codex":[0.9960867,0.001093828,0.0008654394,0.0005432023,0.0009214715,0.0004894052],"domain_scores_gemma":[0.9734788,0.005818064,0.003244807,0.00319313,0.009820794,0.004444444],"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":[0.0003879968,0.0000368012,0.001850318,0.0001916512,0.00004337226,0.0000377139,0.0000234429,0.0001152732,0.0003134101,0.003163459,0.9735113,0.02032522],"study_design_scores_gemma":[0.0005321598,0.0001069179,0.01162818,0.0004331451,0.00008057177,0.0001807301,0.00003867406,0.000971069,0.0006700721,0.002947378,0.9823514,0.00005971869],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.003900799,0.002068319,0.01671071,0.01496169,0.004860621,0.001599934,0.7293493,0.02453044,0.2020183],"genre_scores_gemma":[0.01556231,0.00109654,0.01277537,0.01144566,0.003819117,0.00190407,0.8929558,0.00357779,0.05686336],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.1706246,"threshold_uncertainty_score":0.5707961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02391975055212133,"score_gpt":0.2684759093489843,"score_spread":0.244556158796863,"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."}}