{"id":"W2014968248","doi":"10.1161/circulationaha.106.635011","title":"Defining Obesity Cut Points in a Multiethnic Population","year":2007,"lang":"en","type":"article","venue":"Circulation","topic":"Diabetes, Cardiovascular Risks, and Lipoproteins","field":"Medicine","cited_by":559,"is_retracted":false,"has_abstract":true,"ca_institutions":"Assembly of First Nations; University of Toronto; St. Michael's Hospital","funders":"","keywords":"Medicine; Body mass index; Obesity; Demography; Ethnic group; Risk factor; Population; Type 2 diabetes; Chinese people; Diabetes mellitus; Internal medicine; Gerontology; China; Endocrinology; Environmental health","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.00661869,0.0005152193,0.000408486,0.002216737,0.0008936367,0.001141129,0.0009211831,0.0007324179,0.001051551],"category_scores_gemma":[0.009824395,0.0002124173,0.0006053068,0.001169985,0.0005853907,0.0003936649,0.001291413,0.0009638338,0.0003293806],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000896226,"about_ca_system_score_gemma":0.001089871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008749432,"about_ca_topic_score_gemma":0.01517407,"domain_scores_codex":[0.9980432,0.0008475331,0.0003058599,0.0002057066,0.000437767,0.0001599244],"domain_scores_gemma":[0.9961882,0.001043943,0.0009293924,0.0002542698,0.001168592,0.000415692],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002687882,0.0001052296,0.9879005,0.00004007723,0.00007678294,0.00006589954,0.0006457705,0.0001943393,0.0008180434,0.0002376955,0.0006273033,0.009019589],"study_design_scores_gemma":[0.00004975362,0.0002791747,0.9943038,0.00007802473,0.00008874602,0.0002009677,0.001106506,0.001525866,0.00063387,0.0005416596,0.001173264,0.00001851745],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942409,0.0003888645,0.003153351,0.0002921812,0.00003848898,0.0002102216,0.0003271713,0.00003044676,0.001318337],"genre_scores_gemma":[0.9849619,0.0001738326,0.01270376,0.0002369123,0.00002256285,0.0004865706,0.001140813,0.00001733126,0.0002563715],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008749432,"threshold_uncertainty_score":0.03500342,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01576642287026206,"score_gpt":0.2719529133655358,"score_spread":0.2561864904952738,"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."}}