{"id":"W4353020357","doi":"10.17269/s41997-023-00745-w","title":"Determinants of a decline in a nutrition risk measure differ by baseline high nutrition risk status: targeting nutrition risk screening for frailty prevention in the Canadian Longitudinal Study on Aging (CLSA)","year":2023,"lang":"en","type":"article","venue":"Canadian Journal of Public Health","topic":"Nutrition and Health in Aging","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Research Institute for Aging; University of Waterloo","funders":"Canadian Institutes of Health Research; Government of Canada; Consortium canadien en neurodégénérescence associée au vieillissement","keywords":"Baseline (sea); Medicine; Gerontology; Longitudinal study; Measure (data warehouse); Environmental health; Demography; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.003073867,0.0005321986,0.0004751205,0.000740367,0.00103425,0.0008164233,0.001039522,0.0005843599,0.001287127],"category_scores_gemma":[0.005822559,0.0002286677,0.00172976,0.001713578,0.0002812613,0.0003909634,0.0008049058,0.001287451,0.000118013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005064523,"about_ca_system_score_gemma":0.01407299,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9442365,"about_ca_topic_score_gemma":0.9578335,"domain_scores_codex":[0.9991092,0.0001979561,0.00004675394,0.0001864733,0.0002305411,0.0002289764],"domain_scores_gemma":[0.9980714,0.0002905366,0.0003505187,0.0001618402,0.0007945999,0.0003312351],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001673407,0.0000379437,0.9938658,0.00002670487,0.0001777989,0.00001808991,0.0001034038,0.0001977976,0.00006962254,0.00009914421,0.001046138,0.004190143],"study_design_scores_gemma":[0.00001874487,0.0000350498,0.9978801,0.00002470696,0.0001300181,0.00001620882,0.0001257356,0.001187003,0.00003865517,0.00007177705,0.0004653655,0.000006608437],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9864565,0.001916481,0.001136823,0.001384512,0.00004579728,0.00008183862,0.007381438,0.00003250817,0.001564253],"genre_scores_gemma":[0.9937843,0.0004328621,0.001133478,0.0001630984,0.00001364579,0.00003646408,0.003898748,0.000006136869,0.0005313726],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05576354,"threshold_uncertainty_score":0.1121838,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1831931822306714,"score_gpt":0.4109581271766616,"score_spread":0.2277649449459902,"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."}}