{"id":"W3157532919","doi":"10.1002/mds.28631","title":"Detecting Sensitive Mobility Features for Parkinson's Disease Stages Via Machine Learning","year":2021,"lang":"en","type":"article","venue":"Movement Disorders","topic":"Balance, Gait, and Falls Prevention","field":"Health Professions","cited_by":89,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University; University of Alberta","funders":"Biogen; Michael J. Fox Foundation for Parkinson's Research","keywords":"Parkinson's disease; Gait; STRIDE; Physical medicine and rehabilitation; Discriminative model; Trunk; Wearable computer; Feature (linguistics); Disease; Psychology; Medicine; Artificial intelligence; Computer science; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005705832,0.0001816978,0.0002202834,0.00004328171,0.0009940017,0.00001652232,0.00007202839,0.00009703879,0.00005052113],"category_scores_gemma":[0.0003831234,0.0001788502,0.0001543985,0.0001353562,0.00003499666,0.0001003985,0.0001082329,0.0004527153,0.00001511038],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001326438,"about_ca_system_score_gemma":0.0001038233,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003499234,"about_ca_topic_score_gemma":0.002928179,"domain_scores_codex":[0.9980732,0.0004930315,0.0003071422,0.0004356291,0.000197213,0.0004937779],"domain_scores_gemma":[0.9989485,0.0003605371,0.0001832898,0.0002410376,0.0001306705,0.0001359502],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007033377,0.001553148,0.8875908,0.001735024,0.0002658744,0.00001867698,0.00386615,0.0001457372,0.02692503,0.0009868119,0.004553648,0.07165577],"study_design_scores_gemma":[0.002054733,0.00008791158,0.9508148,0.0001578671,0.00007045383,4.729686e-8,0.006238632,0.003071924,0.0001597121,0.01828443,0.01875634,0.0003031461],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9672855,0.001580466,0.02222591,0.003672954,0.0008661516,0.002073801,0.0002005922,0.000265028,0.001829583],"genre_scores_gemma":[0.9908776,0.0003192187,0.0005742031,0.002967787,0.0001296098,0.000369489,0.0003214476,0.0000343591,0.004406322],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07135262,"threshold_uncertainty_score":0.7645158,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0144194493128102,"score_gpt":0.3222864468654237,"score_spread":0.3078669975526135,"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."}}