{"id":"W2117159123","doi":"10.1016/j.jcmg.2013.02.011","title":"Predictors of Inaccurate Coronary Arterial Stenosis Assessment by CT Angiography","year":2013,"lang":"en","type":"article","venue":"JACC. Cardiovascular imaging","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":89,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Heart, Lung, and Blood Institute; Canadian Institutes of Health Research; National Institute on Aging; European Regional Development Fund; Deutsche Forschungsgemeinschaft; Royal College of Physicians and Surgeons of Canada; Bundesministerium für Bildung und Forschung; GE Healthcare; Toshiba Medical Systems; Donald W. Reynolds Foundation; Doris Duke Charitable Foundation","keywords":"Medicine; Stenosis; Confidence interval; Coronary artery disease; Angiography; Radiology; Cardiology; Computed tomography angiography; Odds ratio; Logistic regression; Internal medicine; Agatston score; Coronary artery calcium","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002001265,0.0004939472,0.0003472485,0.001564961,0.0004373457,0.001524149,0.0007341386,0.001291404,0.00269339],"category_scores_gemma":[0.02895876,0.0004332501,0.0003903984,0.001072407,0.0005593037,0.0008841619,0.0005568434,0.001946419,0.0005677901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003772853,"about_ca_system_score_gemma":0.0005906989,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002248666,"about_ca_topic_score_gemma":0.002687932,"domain_scores_codex":[0.9976972,0.0007435841,0.0003273931,0.0001875641,0.0007102052,0.0003340291],"domain_scores_gemma":[0.9658841,0.01846986,0.008482249,0.002257673,0.002886305,0.002019865],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001140149,0.00001792764,0.9981041,0.000006989075,0.00002276669,0.0002786762,0.0000265837,0.00009870723,0.0001048215,0.00004842283,0.0001320205,0.001044956],"study_design_scores_gemma":[0.00001093305,0.00008604879,0.9880741,0.00005335014,0.0001425739,0.004602768,0.0003141782,0.005369145,0.0005210536,0.0004208905,0.0003879958,0.0000170237],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9933355,0.001849266,0.0007854007,0.0007588116,0.00007921887,0.00001776257,0.0002193264,0.00002682214,0.002927866],"genre_scores_gemma":[0.9992706,0.0001775625,0.0002354957,0.00004704082,0.00007185055,0.000002395884,0.00008766141,0.000006265807,0.0001011261],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00269339,"threshold_uncertainty_score":0.01058388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006464848062636425,"score_gpt":0.2327109359229178,"score_spread":0.2262460878602814,"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."}}