{"id":"W2155105366","doi":"10.1371/journal.pone.0118998","title":"Is Metabolic Syndrome Predictive of Prevalence, Extent, and Risk of Coronary Artery Disease beyond Its Components? Results from the Multinational Coronary CT Angiography Evaluation for Clinical Outcome: An International Multicenter Registry (CONFIRM)","year":2015,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":111,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; University of British Columbia","funders":"National Heart, Lung, and Blood Institute; National Institutes of Health; National Center for Advancing Translational Sciences; National Research Foundation of Korea; National Research Foundation","keywords":"Medicine; Metabolic syndrome; Mace; Internal medicine; Coronary artery disease; Cardiology; Myocardial infarction; Acute coronary syndrome; Revascularization; Percutaneous coronary intervention; Obesity","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":[0.001290929,0.0001612871,0.0004512303,0.0001114823,0.00004833391,0.00001429391,0.0001580089,0.0000526986,0.00002821555],"category_scores_gemma":[0.004484043,0.0001301407,0.0002841917,0.00008992903,0.0002824151,0.0002105851,0.00008121591,0.0001752033,0.000003048827],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002721403,"about_ca_system_score_gemma":0.0001140698,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006374985,"about_ca_topic_score_gemma":0.000002508088,"domain_scores_codex":[0.9974216,0.0002923642,0.000766829,0.0004041195,0.0009764189,0.0001387252],"domain_scores_gemma":[0.995985,0.001622171,0.0005336909,0.0004533368,0.001157374,0.0002484088],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003749295,0.003363437,0.9889988,0.00007923168,0.00222581,0.00001504341,0.0002895647,0.00001823787,0.00008720774,0.00001149369,0.0004177747,0.0007441462],"study_design_scores_gemma":[0.01048968,0.0003291686,0.9523797,0.0003746306,0.005595985,0.00001310553,0.0001556244,0.03025178,0.0001121444,0.0001462693,0.0000438994,0.0001079966],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9799559,0.003832779,0.0000876199,0.0005730596,0.0002676868,0.001428139,0.01376377,0.00001855097,0.00007254251],"genre_scores_gemma":[0.9947385,0.0008953529,0.001845521,0.0001841537,0.0001912867,0.00009553173,0.001973862,0.00001928897,0.00005653937],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03661904,"threshold_uncertainty_score":0.5368143,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1390074313485048,"score_gpt":0.3643762287684387,"score_spread":0.2253687974199339,"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."}}