{"id":"W2058437981","doi":"10.1016/j.gaitpost.2015.01.012","title":"Wavelet-based characterization of gait signal for neurological abnormalities","year":2015,"lang":"en","type":"article","venue":"Gait & Posture","topic":"Parkinson's Disease Mechanisms and Treatments","field":"Medicine","cited_by":53,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Wavelet; Gait; Amyotrophic lateral sclerosis; Physical medicine and rehabilitation; Computer science; Disease; Medicine; Pattern recognition (psychology); Artificial intelligence; Pathology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00008770087,0.0001396735,0.0002486742,0.00005636747,0.00003806292,0.000009765741,0.00005464286,0.000109692,0.00008141398],"category_scores_gemma":[0.00003410314,0.0001043165,0.0001053113,0.00007138694,0.00003008606,0.00004927755,0.00001482146,0.00006997644,0.00001238938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002101551,"about_ca_system_score_gemma":0.0001142672,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006650478,"about_ca_topic_score_gemma":9.068936e-7,"domain_scores_codex":[0.9991896,0.00003133876,0.0001704297,0.0001961634,0.0002194478,0.0001929964],"domain_scores_gemma":[0.9993759,0.00002150764,0.00008890006,0.0001519315,0.00018239,0.0001794151],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.03215172,0.008749892,0.1806549,0.002062965,0.001272853,0.00100872,0.002807779,0.00004018181,0.6749173,0.006341648,0.01637735,0.07361478],"study_design_scores_gemma":[0.01312415,0.006261524,0.8404735,0.0001389688,0.0006198221,0.00007156387,0.000156257,0.004265533,0.04937023,0.001033806,0.08407496,0.0004096505],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953512,0.00009465895,0.001768935,0.001508333,0.0001189847,0.0005297649,0.0002756433,0.00005707398,0.0002953909],"genre_scores_gemma":[0.9954568,0.000004765555,0.00130035,0.001775467,0.0001480276,0.00005788594,0.0008256577,0.00001783214,0.000413221],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6598187,"threshold_uncertainty_score":0.4253901,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02965512610376036,"score_gpt":0.2624601950234825,"score_spread":0.2328050689197221,"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."}}