{"id":"W2146641264","doi":"10.1136/jech-2014-204005","title":"Does waist circumference uncorrelated with BMI add valuable information?","year":2014,"lang":"en","type":"article","venue":"Journal of Epidemiology & Community Health","topic":"Nutritional Studies and Diet","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; The Quebec Population Health Research Network; Centre hospitalier universitaire de Québec","funders":"Drug Applied Research Center, Tabriz University of Medical Sciences","keywords":"Waist; Medicine; Multicollinearity; Body mass index; Obesity; Circumference; Residual; Demography; Statistics; Quartile; Regression analysis; Internal medicine; Mathematics","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":[0.01916565,0.00111918,0.001528731,0.001981878,0.0004438537,0.001970656,0.001434106,0.00130829,0.002683881],"category_scores_gemma":[0.09061455,0.0007403021,0.001399184,0.00394873,0.002673948,0.001760201,0.001146526,0.001244787,0.0005396267],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005281518,"about_ca_system_score_gemma":0.0009412389,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004227936,"about_ca_topic_score_gemma":0.005498117,"domain_scores_codex":[0.9892937,0.006729133,0.0008605634,0.001538718,0.001283459,0.0002943923],"domain_scores_gemma":[0.8719375,0.09182411,0.02065146,0.009744912,0.00476554,0.001076558],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005511502,0.00005443891,0.9582362,0.000371327,0.002464633,0.0004068062,0.0002836001,0.0007879363,0.0004360119,0.000876412,0.0009476644,0.03458381],"study_design_scores_gemma":[0.0000487142,0.0004424445,0.9828067,0.0004580661,0.00160371,0.001330268,0.0003558456,0.004577935,0.0006856016,0.00507723,0.002555298,0.00005822814],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9318874,0.01420392,0.02954217,0.01159658,0.001115827,0.00009225353,0.003422081,0.000147678,0.007992106],"genre_scores_gemma":[0.9906812,0.002062558,0.00449097,0.0008470242,0.0008006404,0.00002229286,0.0007465166,0.00005342051,0.0002954695],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01916565,"threshold_uncertainty_score":0.1013588,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05922039378611201,"score_gpt":0.3656103790967509,"score_spread":0.3063899853106389,"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."}}