{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001695258,0.0003466448,0.0005275054,0.000745013,0.0003476686,0.0007586107,0.0004946155,0.0005579739,0.0006678741],"category_scores_gemma":[0.003913087,0.0003608294,0.0005315474,0.001134738,0.0002470785,0.0004930863,0.0006578483,0.0005110094,0.0001610008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002259437,"about_ca_system_score_gemma":0.0002600704,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004159061,"about_ca_topic_score_gemma":0.007334591,"domain_scores_codex":[0.9993138,0.0002618321,0.00009768127,0.0001559127,0.00009992279,0.00007076632],"domain_scores_gemma":[0.9971293,0.0005291565,0.00137351,0.0004076469,0.0002101642,0.0003502581],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009289868,0.000007870674,0.9995512,0.000001454745,0.00002767301,0.00001293135,0.000007795213,0.00001096124,0.0000462873,0.000003815277,0.00002782369,0.0002092127],"study_design_scores_gemma":[0.000008949043,0.00003908271,0.9996057,0.000002500617,0.00004117369,0.0001062212,0.00002882204,0.0001012081,0.00001631912,0.000007987062,0.00004012557,0.00000186615],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989015,0.0001673164,0.00008005031,0.00004366508,0.00000530238,0.000007782593,0.0005409392,0.000002497207,0.0002508829],"genre_scores_gemma":[0.9987632,0.0000803292,0.000111606,0.00003031975,0.00001989655,0.000009992731,0.0009361748,0.000002041847,0.00004655513],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004159061,"threshold_uncertainty_score":0.008965492,"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."}}