{"id":"W4413247835","doi":"10.2196/77140","title":"Machine Learning Approach for Frailty Detection in Long-Term Care Using Accelerometer-Measured Gait and Daily Physical Activity: Model Development and Validation Study","year":2025,"lang":"en","type":"article","venue":"JMIR Aging","topic":"Frailty in Older Adults","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Accelerometer; Preprint; Gait analysis; Term (time); Gait; Physical activity; Physical medicine and rehabilitation; Computer science; Medicine; World Wide Web","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001866555,0.0001803061,0.0002980186,0.0002766954,0.0001777065,0.00006493075,0.00004288201,0.00006270051,5.223521e-7],"category_scores_gemma":[0.00005457635,0.0001804965,0.00002871171,0.0002290375,0.00002282003,0.0001988867,0.00009110649,0.0002858142,1.286002e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002429967,"about_ca_system_score_gemma":0.00006420758,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004855002,"about_ca_topic_score_gemma":0.00003187787,"domain_scores_codex":[0.9989497,0.00005817516,0.0001662498,0.0004208021,0.0001930078,0.0002120853],"domain_scores_gemma":[0.9996319,0.00005100168,0.00006715677,0.0001336962,0.00007020602,0.00004599275],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002725292,0.0005807825,0.3640967,0.001305225,0.0001051743,0.000006411899,0.01674144,0.003985929,0.04894898,9.469867e-7,8.971075e-7,0.563955],"study_design_scores_gemma":[0.003161769,0.0001029034,0.5106149,0.000250638,0.00008503223,0.000007140534,0.0009046291,0.4664721,0.01823064,0.000006147482,0.000004241996,0.0001599252],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9101586,0.0001161862,0.08803509,0.00002655741,0.00002708369,0.001520809,0.000001730991,0.00005855272,0.00005532833],"genre_scores_gemma":[0.9956172,0.000002451147,0.003960563,0.00001575286,0.00002721574,0.0002110035,0.00003161971,0.00002432729,0.0001098782],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5637951,"threshold_uncertainty_score":0.7360435,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06498903882333722,"score_gpt":0.3466173531625393,"score_spread":0.2816283143392021,"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."}}