{"id":"W4405961472","doi":"10.1093/geroni/igae098.1957","title":"WHO’S SARCOPENIC? AN ANALYSIS USING THE CANADIAN LONGITUDINAL STUDY ON AGING DATA","year":2024,"lang":"en","type":"article","venue":"Innovation in Aging","topic":"Nutrition and Health in Aging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Longitudinal data; Computer science; Data mining","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":[0.01658256,0.0007523266,0.001449587,0.005978471,0.003423799,0.002271807,0.002330444,0.0007930223,0.002831528],"category_scores_gemma":[0.03863041,0.0004492977,0.002292272,0.01614871,0.00089076,0.001029776,0.001605693,0.001745149,0.0002236457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01734609,"about_ca_system_score_gemma":0.03320501,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9853284,"about_ca_topic_score_gemma":0.986263,"domain_scores_codex":[0.9875523,0.003277916,0.001345346,0.001906548,0.004129279,0.001788571],"domain_scores_gemma":[0.9793615,0.00463697,0.003596833,0.001491817,0.009153815,0.001759108],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001908001,0.00002525733,0.9895657,0.0001785437,0.001067319,0.0000823712,0.0004925888,0.0002305171,0.00005719873,0.0005411095,0.003096939,0.004471595],"study_design_scores_gemma":[0.00003243798,0.00003909221,0.9925911,0.000177121,0.0004964515,0.00005252641,0.001361778,0.002324326,0.00005170259,0.0001567309,0.002678304,0.00003834502],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9376065,0.007352619,0.002395771,0.003477703,0.000189573,0.0005206605,0.04241871,0.00007464556,0.005963839],"genre_scores_gemma":[0.987951,0.0009282599,0.001683106,0.0003177899,0.00002489512,0.0001589508,0.008431996,0.00002932976,0.0004747096],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01734609,"threshold_uncertainty_score":0.1258553,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3094573158309297,"score_gpt":0.4828113743370457,"score_spread":0.1733540585061161,"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."}}