{"id":"W4318817889","doi":"10.3390/s23031547","title":"Validation of Inertial Sensors to Evaluate Gait Stability","year":2023,"lang":"en","type":"article","venue":"Sensors","topic":"Balance, Gait, and Falls Prevention","field":"Health Professions","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Inertial measurement unit; Gait; Motion capture; Units of measurement; Stability (learning theory); Intraclass correlation; Gait analysis; Inertial frame of reference; Computer science; Artificial intelligence; Simulation; Motion (physics); Physical medicine and rehabilitation; Mathematics; Physics; Reproducibility; Medicine; Statistics; Machine learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003948206,0.0009114562,0.000387942,0.001036769,0.0003483518,0.0005570063,0.0007037608,0.0007588602,0.0009679256],"category_scores_gemma":[0.009643229,0.0002607096,0.0004190101,0.0006259555,0.0004150534,0.0004692352,0.0006754472,0.0002545951,0.0004701198],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001924795,"about_ca_system_score_gemma":0.0003514101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001194647,"about_ca_topic_score_gemma":0.00156313,"domain_scores_codex":[0.9968257,0.001217661,0.0003670594,0.0003717953,0.001110531,0.0001073769],"domain_scores_gemma":[0.9961163,0.001034353,0.0003674724,0.0003611888,0.002025919,0.00009470007],"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":[0.002898156,0.001063349,0.388559,0.0007570101,0.0004593616,0.0001911055,0.000862536,0.006972421,0.3900904,0.001021919,0.001546966,0.2055777],"study_design_scores_gemma":[0.0003501162,0.01296968,0.6270101,0.0004427576,0.0005387669,0.001256735,0.0009428323,0.09429956,0.2503622,0.001068179,0.01062467,0.0001344416],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8434057,0.001477609,0.1481109,0.0001810406,0.0003123422,0.0007259829,0.001157989,0.0003583653,0.004270134],"genre_scores_gemma":[0.9471286,0.0004799555,0.0496402,0.000187042,0.00008114115,0.0007155316,0.0007701965,0.00004253283,0.0009546911],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003948206,"threshold_uncertainty_score":0.0208804,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06714325239039828,"score_gpt":0.3972995575569151,"score_spread":0.3301563051665168,"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."}}