{"id":"W3117191226","doi":"10.1093/geroni/igaa057.1287","title":"A Time-, Gender-, and Disease-State Invariant Model of Fitness Across the Adult Lifespan","year":2020,"lang":"en","type":"article","venue":"Innovation in Aging","topic":"Behavioral Health and Interventions","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Université Laval; University of Alberta; University of Guelph","funders":"","keywords":"Cardiorespiratory fitness; Equivalence (formal languages); Psychological intervention; Disease; Gerontology; Medicine; Confirmatory factor analysis; Psychology; Physical therapy; Demography; Statistics; Mathematics; Structural equation modeling; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"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":[0.005408749,0.001021769,0.001240251,0.001613467,0.0009443914,0.002208945,0.002234384,0.001615237,0.007245594],"category_scores_gemma":[0.005437717,0.0006626194,0.002835862,0.001229415,0.001674775,0.001459874,0.001658349,0.001977322,0.001355711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0020306,"about_ca_system_score_gemma":0.002564398,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04359669,"about_ca_topic_score_gemma":0.02423578,"domain_scores_codex":[0.9980727,0.0007524789,0.00006606111,0.0006107281,0.0001668441,0.0003312175],"domain_scores_gemma":[0.9978448,0.0008564289,0.000421845,0.0002721492,0.0003028658,0.0003019049],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008922595,0.001722888,0.6193622,0.0002526846,0.002484625,0.001502496,0.002899187,0.2192552,0.003488806,0.08150093,0.006075146,0.06056363],"study_design_scores_gemma":[0.000157869,0.0009226543,0.287212,0.0001885145,0.0005304614,0.0008764149,0.0007353618,0.6501834,0.0002635863,0.05446766,0.004340657,0.0001214153],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8098885,0.0009828185,0.1694455,0.005308169,0.0002815912,0.0004435353,0.003871136,0.0005035106,0.009275224],"genre_scores_gemma":[0.9812796,0.0003287032,0.009936777,0.0002350205,0.00004560075,0.0002960532,0.0008949062,0.00004024966,0.00694314],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04359669,"threshold_uncertainty_score":0.08668584,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1245099962295038,"score_gpt":0.400178677230336,"score_spread":0.2756686810008322,"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."}}