{"id":"W585182724","doi":"10.1007/s12603-015-0553-5","title":"Understanding risk in the oldest old: Frailty and the metabolic syndrome in a chinese community sample aged 90+ years","year":2015,"lang":"en","type":"article","venue":"The journal of nutrition health & aging","topic":"Frailty in Older Adults","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nova Scotia Health Authority; Dalhousie University","funders":"","keywords":"Metabolic syndrome; Medicine; Hazard ratio; Confidence interval; Demography; Frailty Index; Odds ratio; Gerontology; Epidemiology; Internal medicine; Obesity","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":[0.001233448,0.0003470954,0.0003482789,0.001234051,0.0006028986,0.0005589745,0.0004363157,0.0004415582,0.0009155139],"category_scores_gemma":[0.002064151,0.0001884854,0.0003847078,0.001052158,0.0002638559,0.0005315621,0.0005793094,0.0003479779,0.00007900074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003633098,"about_ca_system_score_gemma":0.0006797849,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05313112,"about_ca_topic_score_gemma":0.07146955,"domain_scores_codex":[0.9997167,0.00008023706,0.00002984487,0.00005381034,0.00005681759,0.00006258667],"domain_scores_gemma":[0.999486,0.00006446006,0.0002055378,0.00004319381,0.00007561946,0.0001251278],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003743659,0.00002738886,0.9979381,0.000009969937,0.00003294681,0.00002847458,0.0001484203,0.00002392099,0.00006894502,0.00001100253,0.00004223915,0.001631069],"study_design_scores_gemma":[0.000002135735,0.00002799973,0.9996644,0.000003904918,0.00001566477,0.0000198114,0.0001329925,0.00006930233,0.000009488494,0.00001765845,0.0000351329,0.000001461388],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.999238,0.0002855561,0.00006006544,0.00006108871,0.000003731285,0.00000961641,0.0001540301,0.000001233381,0.0001867244],"genre_scores_gemma":[0.9995039,0.000142619,0.0000724439,0.0000298602,0.000007080688,0.000008876371,0.0001295453,3.628769e-7,0.00010543],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05313112,"threshold_uncertainty_score":0.1056437,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1462482640318156,"score_gpt":0.3622648701941447,"score_spread":0.2160166061623291,"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."}}