{"id":"W4409245564","doi":"10.2196/65629","title":"Model-Based Feature Extraction and Classification for Parkinson Disease Screening Using Gait Analysis: Development and Validation Study","year":2025,"lang":"en","type":"article","venue":"JMIR Aging","topic":"Balance, Gait, and Falls Prevention","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Gait; Physical medicine and rehabilitation; Kinematics; Gait analysis; Parkinson's disease; Trunk; STRIDE; Feature (linguistics); Computer science; Artificial intelligence; Medicine; Disease; Pathology; Biology","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":[0.0006153496,0.0001194759,0.0001739618,0.0003012863,0.0008916344,0.00004039,0.00004090613,0.00008591522,0.00000101306],"category_scores_gemma":[0.0000319618,0.0001199782,0.00003974524,0.0003354679,0.00001286762,0.0002080271,0.00002840622,0.0001833216,4.133219e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001140787,"about_ca_system_score_gemma":0.0001387291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001340798,"about_ca_topic_score_gemma":0.00005235071,"domain_scores_codex":[0.9988719,0.0001769251,0.0002883368,0.0003436861,0.0001242551,0.0001948674],"domain_scores_gemma":[0.999364,0.0001116491,0.0002030383,0.0001489629,0.0001018785,0.00007051935],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002349874,0.0003511581,0.9628263,0.0006273273,0.0002109788,7.84609e-7,0.001979694,0.001293215,0.004856367,0.0001874858,0.0002123466,0.0272194],"study_design_scores_gemma":[0.0006690102,0.000005471938,0.5774788,0.000171355,0.0002756758,2.813777e-8,0.001086583,0.4196062,0.000007357174,0.00008397544,0.0005432683,0.00007220134],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6286858,0.0001183851,0.3697223,0.0002182163,0.00005756527,0.001094715,0.000004945846,0.00004618452,0.00005186995],"genre_scores_gemma":[0.9833086,0.000007877593,0.01540188,0.0001369734,0.00004772254,0.0005118512,0.0001472978,0.00001108725,0.0004267722],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.418313,"threshold_uncertainty_score":0.6857821,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0773467644123984,"score_gpt":0.4235724482513907,"score_spread":0.3462256838389923,"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."}}