{"id":"W2118655856","doi":"10.1093/ageing/aft004","title":"Co-occurrence of cardiometabolic diseases and frailty in older Chinese adults in the Beijing Longitudinal Study of Ageing","year":2013,"lang":"en","type":"article","venue":"Age and Ageing","topic":"Frailty in Older Adults","field":"Medicine","cited_by":64,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Canadian Institutes of Health Research; National Natural Science Foundation of China","keywords":"Medicine; Gerontology; Hazard ratio; Longitudinal study; Cohort; Population ageing; Cohort study; Ageing; Proportional hazards model; Stroke (engine); Population; Demography; Environmental health; Internal medicine; Confidence interval","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":[0.0001956318,0.0001486886,0.0004494294,0.0002119058,0.00004142318,0.00002332419,0.00009851541,0.0000369485,0.00001336502],"category_scores_gemma":[0.0002718357,0.00009926807,0.00003783222,0.0004090712,0.00009604586,0.0001908883,0.00005884606,0.0001923685,6.874485e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008496765,"about_ca_system_score_gemma":0.0000136753,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003223028,"about_ca_topic_score_gemma":0.0006518969,"domain_scores_codex":[0.998853,0.00009465887,0.0003487768,0.0002518204,0.0002527274,0.0001990431],"domain_scores_gemma":[0.9993081,0.0002500778,0.00009493304,0.0002459252,0.00004030947,0.00006062832],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002806514,0.0003342443,0.9608986,0.0002911222,0.00002878851,0.001700084,0.01261332,0.000007777032,0.0004755298,0.000002666734,0.0000233435,0.02359639],"study_design_scores_gemma":[0.002536641,0.0001657844,0.9914681,0.0006244975,0.00005357841,0.00001672852,0.00484333,0.0001416404,0.00001775287,0.00003123334,0.000008825685,0.00009182875],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997436,0.001543922,0.000009283559,0.00008165053,0.0000334247,0.0007352643,0.0000137155,0.000009091228,0.0001376276],"genre_scores_gemma":[0.9996773,0.0001329372,0.00003276472,0.00004676677,0.0000438535,0.00003817096,0.00001066739,0.000007724369,0.000009785698],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03056949,"threshold_uncertainty_score":0.4872275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02223183158894135,"score_gpt":0.3056299620665103,"score_spread":0.2833981304775689,"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."}}