{"id":"W3178743384","doi":"10.1093/gerona/glab192","title":"Getting a Grip on Secular Changes: Age–Period–Cohort Modeling of Grip Strength in the English Longitudinal Study of Ageing","year":2021,"lang":"en","type":"article","venue":"The Journals of Gerontology Series A","topic":"Nutrition and Health in Aging","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"National Institute on Aging","keywords":"Grip strength; Cohort; Cohort effect; Ageing; Gerontology; Cohort study; Population; Demography; Population ageing; Medicine; Secular variation; Life course approach; Psychology; Physical therapy; Developmental psychology; Environmental health; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01949478,0.0008069582,0.001058092,0.001231811,0.0007190343,0.001578405,0.002176631,0.0009763672,0.002385196],"category_scores_gemma":[0.02013958,0.0006267519,0.003117553,0.001293754,0.0006334531,0.0009288622,0.001626804,0.001252944,0.000322749],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001265841,"about_ca_system_score_gemma":0.00205103,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1240427,"about_ca_topic_score_gemma":0.08384723,"domain_scores_codex":[0.9955723,0.003171758,0.0001402809,0.0007068475,0.0001759572,0.0002327987],"domain_scores_gemma":[0.987502,0.00902268,0.00117055,0.001103233,0.0007770374,0.000424457],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007652385,0.0003014457,0.6194046,0.0001905578,0.004378407,0.0006653886,0.002799039,0.3246538,0.0007143982,0.01409983,0.002770991,0.02925628],"study_design_scores_gemma":[0.00008268984,0.0002862448,0.10248,0.00008925526,0.0009120365,0.0001240204,0.0006486545,0.8862397,0.0001368335,0.006937955,0.002004676,0.00005796353],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8935367,0.00127295,0.09981129,0.001541321,0.0001249372,0.0002828596,0.00167441,0.0002000292,0.001555531],"genre_scores_gemma":[0.9783338,0.0004562422,0.01707998,0.0001729605,0.00004321238,0.0003140278,0.0009062775,0.00003140136,0.002661956],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1240427,"threshold_uncertainty_score":0.2466413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.129455664183954,"score_gpt":0.3775850675038303,"score_spread":0.2481294033198762,"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."}}