{"id":"W3186351744","doi":"10.1016/j.ypmed.2021.106739","title":"Clustering of obesity-related characteristics: A latent class analysis from the Canadian Longitudinal Study on Aging","year":2021,"lang":"en","type":"article","venue":"Preventive Medicine","topic":"Nutritional Studies and Diet","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University; Population Health Research Institute; McMaster University; Health Sciences North; Impact","funders":"Canadian Institutes of Health Research; Canada Foundation for Innovation; Government of Canada","keywords":"Medicine; Obesity; Waist; Body mass index; Odds ratio; Confidence interval; Latent class model; Logistic regression; Odds; Demography; Gerontology; Internal medicine; Statistics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.005827994,0.000714318,0.001098109,0.003102458,0.005544535,0.002430761,0.002971356,0.001203496,0.002196074],"category_scores_gemma":[0.01320631,0.0005184016,0.002231966,0.006300183,0.00131051,0.000712865,0.001633976,0.002108574,0.0002417783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01212489,"about_ca_system_score_gemma":0.01961613,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9703067,"about_ca_topic_score_gemma":0.9781431,"domain_scores_codex":[0.9971968,0.0008079554,0.0001464381,0.0005377567,0.000619839,0.0006911731],"domain_scores_gemma":[0.9931706,0.001456437,0.0009486261,0.0009435645,0.002480406,0.001000424],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002859093,0.0001405508,0.9839661,0.0000379837,0.0005323291,0.0000486888,0.002404315,0.001102304,0.0002118605,0.0008607779,0.002265473,0.008143653],"study_design_scores_gemma":[0.00002116323,0.00002474089,0.9892865,0.00003982869,0.0001946454,0.0000259111,0.002251702,0.006880994,0.00003940565,0.0004458389,0.0007550414,0.00003430159],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946998,0.0005379737,0.001326729,0.0004122613,0.0000222061,0.00006522622,0.002482353,0.00001917673,0.0004344039],"genre_scores_gemma":[0.9941615,0.0002467178,0.001112026,0.00004784936,0.00000965198,0.00004527458,0.003831843,0.00001689954,0.0005281912],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02969331,"threshold_uncertainty_score":0.0879727,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04924901749406081,"score_gpt":0.314981624687781,"score_spread":0.2657326071937202,"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."}}