{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001126672,0.0006420944,0.0006688263,0.002044413,0.0001826405,0.0006967291,0.0003465976,0.0006021406,0.0006820984],"category_scores_gemma":[0.003879778,0.0001346119,0.000532927,0.0009196505,0.0002661549,0.0005205495,0.0003963239,0.0004463245,0.0002633618],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002991109,"about_ca_system_score_gemma":0.0002488839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001290956,"about_ca_topic_score_gemma":0.001613409,"domain_scores_codex":[0.9995641,0.0001203249,0.00005834276,0.0001306083,0.00007313384,0.00005345312],"domain_scores_gemma":[0.9978845,0.00112624,0.0005610595,0.00008701759,0.0002443948,0.00009693822],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006075247,0.0004636801,0.8168458,0.000186295,0.0003115609,0.0002092547,0.0001409798,0.01687115,0.01082086,0.0001903938,0.001013425,0.1523391],"study_design_scores_gemma":[0.00006283847,0.0007032003,0.6838959,0.0001182879,0.0002024458,0.0007763901,0.0002775028,0.3030753,0.007407861,0.002500358,0.00091737,0.0000626801],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9689888,0.000829001,0.02820693,0.0001855981,0.00002596027,0.00008761132,0.0007575937,0.0002153027,0.0007031069],"genre_scores_gemma":[0.9902515,0.0001114894,0.008998504,0.00002478347,0.00001686589,0.00004073726,0.0004364269,0.000005185479,0.0001144923],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002044413,"threshold_uncertainty_score":0.005958498,"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."}}