{"id":"W4310070887","doi":"10.1016/j.jacr.2022.09.012","title":"CAD-RADS™ 2.0 – 2022 Coronary Artery Disease – Reporting and Data System.","year":2022,"lang":"en","type":"article","venue":"Journal of the American College of Radiology","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"British Heart Foundation","keywords":"Medicine; Coronary artery disease; Stenosis; Fractional flow reserve; CAD; Radiology; Cardiology; Internal medicine; 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":[0.004328862,0.0008147059,0.001367578,0.004116539,0.0005016171,0.002453244,0.001918037,0.001281813,0.07511674],"category_scores_gemma":[0.0187061,0.0006836258,0.0008332367,0.004525733,0.0003467833,0.001503428,0.001502038,0.001910665,0.06387661],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001469775,"about_ca_system_score_gemma":0.003917534,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01047215,"about_ca_topic_score_gemma":0.01052199,"domain_scores_codex":[0.9968597,0.0008905721,0.0007835965,0.0004269859,0.0006790549,0.0003601697],"domain_scores_gemma":[0.9831234,0.003363554,0.002727773,0.001851456,0.006366239,0.002567454],"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":[0.0008196218,0.00004956433,0.005000226,0.0002884027,0.00008169478,0.00005145045,0.00003294029,0.0002048127,0.0004041916,0.003140383,0.9678608,0.022066],"study_design_scores_gemma":[0.0009020161,0.0001856557,0.03711445,0.0006749828,0.0001910244,0.0003209005,0.00007711357,0.00177971,0.001047423,0.004086428,0.9535252,0.00009502298],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.005664831,0.002184168,0.009157793,0.007761097,0.002080569,0.001074639,0.8647975,0.01255608,0.09472328],"genre_scores_gemma":[0.01577978,0.0007665109,0.007915854,0.00561062,0.001327221,0.001122773,0.9434345,0.001194117,0.02284872],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.07511674,"threshold_uncertainty_score":0.2512905,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0194226257173811,"score_gpt":0.2914613020820269,"score_spread":0.2720386763646458,"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."}}