{"id":"W4296664047","doi":"10.1148/ryct.220183","title":"CAD-RADS™ 2.0 – 2022 Coronary Artery Disease – Reporting and Data System An Expert Consensus Document of the Society of Cardiovascular Computed Tomography (SCCT), the American College of Cardiology (ACC), the American College of Radiology (ACR) and the North America Society of Cardiovascular Imaging (NASCI)","year":2022,"lang":"en","type":"article","venue":"Radiology Cardiothoracic Imaging","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":126,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"British Heart Foundation","keywords":"Medicine; Coronary artery disease; Stenosis; Fractional flow reserve; CAD; Radiology; Cardiology; Internal medicine; Computed tomography angiography; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.007276064,0.0005964204,0.004668551,0.0001854364,0.0007248075,0.00001102894,0.001110434,0.00006160546,0.000001456848],"category_scores_gemma":[0.0006614699,0.0003691867,0.004021057,0.001557806,0.01486976,0.00009156377,0.001746744,0.0008825695,6.253948e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001981513,"about_ca_system_score_gemma":0.000652667,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001740722,"about_ca_topic_score_gemma":0.000003408982,"domain_scores_codex":[0.9899812,0.004836092,0.002191277,0.001183832,0.001070651,0.0007369522],"domain_scores_gemma":[0.9890216,0.002567483,0.003330528,0.004343461,0.0005427666,0.000194137],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002079376,0.0001444373,0.8901817,0.001378872,0.03955387,0.0006429082,0.004526074,0.03262984,0.001574417,0.000145322,0.01334957,0.01379361],"study_design_scores_gemma":[0.008653608,0.000720965,0.7183327,0.0005350854,0.02492383,0.03524871,0.1236187,0.06862362,0.0004393655,0.00008538159,0.01759889,0.001219134],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8446669,0.141733,0.004007753,0.002973448,0.0007027813,0.002141055,0.003667252,0.00006270259,0.00004508154],"genre_scores_gemma":[0.9938681,0.003619455,0.001258835,0.0006098378,0.000284614,0.0001363292,0.0001414765,0.00007771752,0.000003710095],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.171849,"threshold_uncertainty_score":0.999876,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01368656268633364,"score_gpt":0.2723007305180378,"score_spread":0.2586141678317042,"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."}}