{"id":"W2261388433","doi":"10.1016/j.jcct.2016.01.005","title":"Total coronary atherosclerotic plaque burden assessment by CT angiography for detecting obstructive coronary artery disease associated with myocardial perfusion abnormalities","year":2016,"lang":"en","type":"article","venue":"Journal of cardiovascular computed tomography","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ottawa Hospital; University of Ottawa","funders":"National Heart, Lung, and Blood Institute","keywords":"Medicine; Coronary artery disease; Atheroma; Cardiology; Internal medicine; Radiology; Angiography; Population; Receiver operating characteristic; Stenosis; Computed tomography angiography","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"],"consensus_categories":[],"category_scores_codex":[0.0009134448,0.0004436044,0.001222304,0.0006488512,0.0002267405,0.00008126499,0.0001668852,0.00009909345,0.000008168322],"category_scores_gemma":[0.0001933881,0.0003098313,0.005432036,0.0005806989,0.0002717628,0.0003257326,0.00006923925,0.0003687416,9.901244e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002024547,"about_ca_system_score_gemma":0.0002891353,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001155859,"about_ca_topic_score_gemma":3.742929e-7,"domain_scores_codex":[0.9967446,0.0003497314,0.0006689189,0.000423006,0.001262935,0.0005507485],"domain_scores_gemma":[0.9967176,0.0008791977,0.0004403657,0.0004950412,0.0009435485,0.0005242679],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002962225,0.0005604597,0.8918166,0.0001862061,0.04110577,0.003206092,0.0003189914,0.004770719,0.001098828,0.00002745361,0.00358002,0.05036667],"study_design_scores_gemma":[0.01338699,0.001542422,0.9697958,0.001647736,0.0074923,0.003156259,0.0003122415,0.0002685549,0.0002551024,0.0001119936,0.001498425,0.0005321943],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9297029,0.01277521,0.05506339,0.0002605927,0.000924441,0.0008441564,0.0002428506,0.0001046284,0.00008182514],"genre_scores_gemma":[0.9963154,0.0002508511,0.002342665,0.00008495001,0.0008128058,0.00003139686,0.00006473617,0.00008354059,0.0000136468],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07797921,"threshold_uncertainty_score":0.9999354,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007696740581636012,"score_gpt":0.2161107703269109,"score_spread":0.2084140297452749,"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."}}