{"id":"W4405976689","doi":"10.1093/geroni/igae098.0740","title":"UNIFIED FRAMEWORK FOR MEASURING MOBILITY IN OLDER PEOPLE: EMERGING DATA FROM A CANADIAN AGING COHORT","year":2024,"lang":"en","type":"article","venue":"Innovation in Aging","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Cohort; Gerontology; Older people; Aging in place; Computer science; Psychology; 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":[0.01711687,0.0007093307,0.001041453,0.006988157,0.004127252,0.003203007,0.003615431,0.0008425348,0.001424079],"category_scores_gemma":[0.02488059,0.0002885737,0.001713158,0.01441213,0.001379071,0.0009248076,0.004271109,0.001740498,0.0002786846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03801223,"about_ca_system_score_gemma":0.06036437,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9872776,"about_ca_topic_score_gemma":0.9915862,"domain_scores_codex":[0.9913825,0.001606274,0.0008238668,0.001284807,0.004104992,0.0007975982],"domain_scores_gemma":[0.9798038,0.001216453,0.001345601,0.001047262,0.01521189,0.001375017],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001555675,0.00006081991,0.8861577,0.0006735435,0.0005262614,0.00011576,0.005524139,0.0009297361,0.0003129327,0.008269178,0.02750034,0.06977392],"study_design_scores_gemma":[0.00003232243,0.00004532186,0.9690332,0.0007716487,0.0002910482,0.00008099338,0.003045213,0.002161254,0.000139485,0.001509652,0.02278455,0.0001054824],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6592206,0.03452419,0.05912032,0.02171873,0.001192725,0.003613133,0.181385,0.0005661974,0.03865916],"genre_scores_gemma":[0.8737251,0.009470294,0.05639644,0.00196802,0.0001474361,0.002458759,0.05304206,0.0000923156,0.002699501],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03801223,"threshold_uncertainty_score":0.2757993,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08722261304870692,"score_gpt":0.3957765723596232,"score_spread":0.3085539593109162,"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."}}