{"id":"W1919836900","doi":"10.1002/oby.20102","title":"Differences in subcutaneous abdominal adiposity regions in four ethnic groups","year":2013,"lang":"en","type":"article","venue":"Obesity","topic":"Diabetes, Cardiovascular Risks, and Lipoproteins","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Institute of Nutrition, Metabolism and Diabetes; Simon Fraser University","funders":"Canadian Institutes of Health Research","keywords":"Medicine; Confounding; Ethnic group; Adipose tissue; Subcutaneous fat; Body fat distribution; Cohort; Demography; South asia; Subcutaneous adipose tissue; Abdominal fat; Fat mass; Anthropometry; Internal medicine; Obesity","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003655454,0.0001780093,0.0005739073,0.0001667436,0.00005289177,0.00002257139,0.000153409,0.0001648641,0.0001937153],"category_scores_gemma":[0.0001320645,0.0001561251,0.0002166336,0.0003193943,0.00009705197,0.0001177469,0.00006325256,0.0004282033,0.0002382182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001208121,"about_ca_system_score_gemma":0.00005687643,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03125771,"about_ca_topic_score_gemma":0.02378337,"domain_scores_codex":[0.9985196,0.000163251,0.0002603463,0.0003433384,0.0003047818,0.0004086703],"domain_scores_gemma":[0.9991835,0.00008383798,0.00005074099,0.0004617313,0.00005244543,0.0001677345],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001132899,0.000435856,0.8373086,0.0001304893,0.0001154847,0.0009007202,0.0007090961,0.000002527893,0.0002878144,0.0001170839,0.0004305418,0.1594484],"study_design_scores_gemma":[0.001089327,0.0001834239,0.9964576,0.0001473731,0.00007180777,0.0001700251,0.0001118708,0.0001612877,0.0002657549,0.0009531617,0.0002150809,0.0001732798],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951941,0.001476316,0.0001337105,0.0003947337,0.0001217959,0.0007031051,0.000002616827,0.00005260892,0.001921041],"genre_scores_gemma":[0.998513,0.0002038583,0.0003511083,0.000160789,0.0001378329,0.00006869886,0.000006642926,0.00001565293,0.0005423454],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1592752,"threshold_uncertainty_score":0.9940301,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02613848392399121,"score_gpt":0.2387904100435334,"score_spread":0.2126519261195422,"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."}}