{"id":"W1990758640","doi":"10.1186/1471-2288-12-115","title":"Predicting waist circumference from body mass index","year":2012,"lang":"en","type":"article","venue":"BMC Medical Research Methodology","topic":"Diabetes, Cardiovascular Risks, and Lipoproteins","field":"Medicine","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"Purdue Pharma (Canada)","funders":"Sanofi","keywords":"Waist; Medicine; National Health and Nutrition Examination Survey; Body mass index; Overweight; Abdominal obesity; Circumference; Demography; Obesity; Population; Gerontology; Internal medicine; Environmental health; Mathematics","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":[0.001832299,0.000921348,0.0003790274,0.001010715,0.0001671836,0.000668711,0.0003934053,0.0003755365,0.001710534],"category_scores_gemma":[0.009654429,0.0002882874,0.0005625015,0.0007610643,0.0002201487,0.0003058075,0.0003566689,0.0008026261,0.001168942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003638567,"about_ca_system_score_gemma":0.0009011148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01427695,"about_ca_topic_score_gemma":0.009920974,"domain_scores_codex":[0.9993178,0.0002801314,0.00005619859,0.000146986,0.0001496861,0.00004914235],"domain_scores_gemma":[0.997067,0.001698746,0.0004554744,0.0001783024,0.0004882223,0.0001121395],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001645907,0.0001209235,0.9663582,0.00006826076,0.0002080388,0.00009245762,0.0000555743,0.01183024,0.0005255596,0.0001011262,0.00170382,0.01877119],"study_design_scores_gemma":[0.00009563498,0.000512274,0.7905301,0.0002061101,0.0004129727,0.0006151844,0.0001171722,0.2022182,0.001355199,0.001106321,0.002780509,0.00005018708],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9466372,0.001342837,0.04224944,0.0007976198,0.0001340977,0.0002497541,0.00315217,0.0005755574,0.004861353],"genre_scores_gemma":[0.986667,0.0004225195,0.01006674,0.0001085695,0.00004190124,0.00009029881,0.001813465,0.00003060494,0.0007590348],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01427695,"threshold_uncertainty_score":0.02838773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4017367060840137,"score_gpt":0.4981967469124098,"score_spread":0.0964600408283961,"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."}}