{"id":"W3042339091","doi":"10.1016/j.dsx.2020.05.043","title":"Prevalence of Metabolic Syndrome by different definitions, and its association with type 2 diabetes, pre-diabetes, and cardiovascular disease risk in Brazil","year":2020,"lang":"en","type":"article","venue":"Diabetes & Metabolic Syndrome Clinical Research & Reviews","topic":"Diabetes, Cardiovascular Risks, and Lipoproteins","field":"Medicine","cited_by":84,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Global Health Research","funders":"Universitetet i Oslo","keywords":"Medicine; Diabetes mellitus; Metabolic syndrome; National Cholesterol Education Program; Internal medicine; Disease; Type 2 diabetes; Type 2 Diabetes Mellitus; Anthropometry; Population; Cross-sectional study; Environmental health; Endocrinology; Pathology","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":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.01558562,0.000754379,0.00526933,0.0004404126,0.0002152236,0.000127615,0.0005516968,0.0004246132,0.000154603],"category_scores_gemma":[0.02491691,0.0005812718,0.00126598,0.001957468,0.0005902426,0.0004301147,0.0004943915,0.002026366,0.00009198585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006864871,"about_ca_system_score_gemma":0.0003288506,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001362031,"about_ca_topic_score_gemma":0.00001353467,"domain_scores_codex":[0.9858122,0.005875855,0.002230688,0.00187372,0.002561445,0.001646031],"domain_scores_gemma":[0.9930253,0.002117335,0.0006279455,0.001633128,0.000677886,0.001918373],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001156882,0.0006013926,0.8649036,0.004566047,0.003565255,0.00004638564,0.00009007076,0.000004951346,0.00008663874,0.00004696533,0.0006832647,0.1252897],"study_design_scores_gemma":[0.003234593,0.001371146,0.9242871,0.001814801,0.004566162,0.000006421243,0.00001611121,0.0003452742,0.0003045961,0.0001319584,0.06336545,0.0005563704],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.541198,0.455681,0.000003024697,0.0002416103,0.00007558928,0.002484045,0.0002486903,0.00004090386,0.00002713512],"genre_scores_gemma":[0.6161993,0.3823618,0.0001534792,0.0002987375,0.0001144926,0.0006110225,0.00009368898,0.00008141312,0.00008609545],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1247333,"threshold_uncertainty_score":0.9996639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07553873778588288,"score_gpt":0.3490795985485241,"score_spread":0.2735408607626412,"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."}}