{"id":"W2868619500","doi":"10.1089/met.2017.0177","title":"Should Waist Circumference Cutoffs in the Context of Cardiometabolic Risk Factor Assessment be Specific to Sex, Age, and BMI?","year":2018,"lang":"en","type":"article","venue":"Metabolic Syndrome and Related Disorders","topic":"Diabetes, Cardiovascular Risks, and Lipoproteins","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke; Health and Social Services Centre University Institute of Geriatrics of Sherbrooke","funders":"","keywords":"Medicine; Waist; Body mass index; Context (archaeology); Overweight; Logistic regression; Metabolic syndrome; Risk assessment; Risk factor; Obesity; Receiver operating characteristic; Odds ratio; Demography; Internal medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.0009095572,0.0003394939,0.001228961,0.0004563007,0.0001641784,0.00005671142,0.0002027997,0.0002230941,0.0001103802],"category_scores_gemma":[0.0001132807,0.0002331397,0.0002833716,0.000972079,0.0005305484,0.0001059156,0.00009205673,0.0004998212,0.00001710289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001902769,"about_ca_system_score_gemma":0.00006835637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005388869,"about_ca_topic_score_gemma":0.0005480205,"domain_scores_codex":[0.9974959,0.0003486276,0.0005299395,0.0005682237,0.0005959328,0.0004614049],"domain_scores_gemma":[0.9987559,0.0001035941,0.0001300176,0.0007192469,0.00007584628,0.0002153708],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00006492973,0.0003359457,0.04550775,0.0001068375,0.001707681,0.0001216148,0.008414485,0.000005385403,0.0003539337,0.0006762012,0.0003722182,0.942333],"study_design_scores_gemma":[0.002458818,0.0003615815,0.861149,0.00007678631,0.0005592072,0.0001723848,0.003080883,0.00002541529,0.0001329959,0.0002814669,0.1314214,0.0002800957],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.971741,0.02093717,0.0001090416,0.0006298399,0.0003065942,0.001197801,0.00007689063,0.00004249697,0.004959154],"genre_scores_gemma":[0.9831377,0.01591188,0.0001474037,0.0003124018,0.00006923705,0.00006762048,0.00001989601,0.00003971411,0.000294098],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9420529,"threshold_uncertainty_score":0.9507159,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02130518908391242,"score_gpt":0.2748021260881445,"score_spread":0.253496937004232,"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."}}