{"id":"W2913306983","doi":"10.1161/circimaging.118.007940","title":"Predictive Model for High-Risk Coronary Artery Disease","year":2019,"lang":"en","type":"article","venue":"Circulation Cardiovascular Imaging","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal Heart Institute; University of British Columbia","funders":"National Heart, Lung, and Blood Institute","keywords":"Medicine; Coronary artery disease; Internal medicine; Cardiology; Stenosis; CAD; Chest pain; Odds ratio; Radiology","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":[],"consensus_categories":[],"category_scores_codex":[0.0004631678,0.000211218,0.0004757471,0.0001461675,0.0001205335,0.00004820446,0.00006145168,0.00004658272,0.00001407891],"category_scores_gemma":[0.0003552972,0.0002244597,0.001150213,0.0001336107,0.00005434053,0.0002333935,0.00003840043,0.0001684546,0.00007183634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001631962,"about_ca_system_score_gemma":0.0001809876,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001601105,"about_ca_topic_score_gemma":1.255907e-7,"domain_scores_codex":[0.9983239,0.00006228005,0.0002581904,0.0005321379,0.0005070638,0.0003164035],"domain_scores_gemma":[0.998373,0.0001513725,0.0000732659,0.0008578897,0.0003122344,0.0002322806],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001339311,0.00004496392,0.6672357,0.0001337551,0.0009902063,0.00004684423,0.0001300536,0.3189721,0.00009751459,0.0001471777,0.0005691416,0.01149864],"study_design_scores_gemma":[0.002226271,0.00001014852,0.5030324,0.00007237939,0.001677644,0.0000621616,0.00004094969,0.4914828,0.00002107186,0.0007770854,0.0004286646,0.0001683686],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3841291,0.005240678,0.6073466,0.0002301561,0.0006314223,0.001427015,0.00014933,0.0002243249,0.0006213631],"genre_scores_gemma":[0.9966886,0.00005583026,0.001781974,0.0003867995,0.0003967893,0.0001148289,0.0003918361,0.00006938386,0.0001139542],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6125595,"threshold_uncertainty_score":0.9153199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01010762079073448,"score_gpt":0.2295630008375898,"score_spread":0.2194553800468553,"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."}}