{"id":"W2127067865","doi":"10.1016/j.amjcard.2010.08.015","title":"Usefulness of Hypertriglyceridemic Waist Phenotype in Type 2 Diabetes Mellitus to Predict the Presence of Coronary Artery Disease as Assessed by Computed Tomographic Coronary Angiography","year":2010,"lang":"en","type":"article","venue":"The American Journal of Cardiology","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":48,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval","funders":"Servier; Ministry of Economic Affairs; Stichting voor de Technische Wetenschappen; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Astellas Pharma; Hartstichting; Boston Scientific Corporation","keywords":"Waist; Medicine; Internal medicine; Coronary artery disease; Odds ratio; Circumference; Cardiology; Confidence interval; Diabetes mellitus; Waist-to-height ratio; Triglyceride; Body mass index; Cholesterol; Endocrinology; Geometry","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":[0.0008304177,0.0001801177,0.001005655,0.0002912126,0.00004278882,0.00000689676,0.000396919,0.000045913,0.000007107613],"category_scores_gemma":[0.0008289294,0.0001080234,0.0004922217,0.0009566587,0.001454307,0.00005115952,0.00008553681,0.000532392,0.000001666137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001443287,"about_ca_system_score_gemma":0.0002537609,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005438732,"about_ca_topic_score_gemma":0.000001719196,"domain_scores_codex":[0.9981372,0.000488001,0.0005692404,0.0001729969,0.0003391806,0.0002933693],"domain_scores_gemma":[0.9961604,0.002140563,0.0005069547,0.0005513799,0.0004243036,0.0002164073],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002032651,0.00009853375,0.9729264,0.00002744633,0.0006636592,0.000130415,0.0001342349,0.0007856569,0.01363742,0.00002467291,0.002967602,0.006571342],"study_design_scores_gemma":[0.0007886623,0.001405264,0.9947641,0.000115228,0.0005972872,0.0004282255,0.0002393278,0.00009252573,0.0004479115,0.000225501,0.0007873718,0.0001085503],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9923108,0.004823077,0.0002445208,0.001500095,0.0007052812,0.0002730263,0.00005288383,0.00001199885,0.0000783709],"genre_scores_gemma":[0.9985684,0.0003944706,0.0001400806,0.0005986064,0.0002535064,0.000007994079,0.00001251881,0.00002167191,0.000002766266],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02183778,"threshold_uncertainty_score":0.5358456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009268756454432014,"score_gpt":0.2494801362050253,"score_spread":0.2402113797505933,"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."}}