{"id":"W4387430212","doi":"10.1007/978-3-031-46005-0_23","title":"Pose2Gait: Extracting Gait Features from Monocular Video of Individuals with Dementia","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Balance, Gait, and Falls Prevention","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ontario Brain Institute; Toronto Western Hospital; Hospital for Sick Children; University of Toronto; University Health Network; Toronto Rehabilitation Institute","funders":"","keywords":"Computer science; Artificial intelligence; Gait; Monocular; Computer vision; Dementia; Physical medicine and rehabilitation; 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":[0.0001697918,0.0007736931,0.000443841,0.001153978,0.0001498237,0.0003990451,0.0003352788,0.0004162885,0.006131071],"category_scores_gemma":[0.0004117374,0.0001742741,0.0003553353,0.0008129753,0.00006823566,0.0002942345,0.0004203469,0.0001464529,0.002986493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001505427,"about_ca_system_score_gemma":0.0002429095,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00725987,"about_ca_topic_score_gemma":0.02253553,"domain_scores_codex":[0.9999154,0.000007272904,0.000004310574,0.00002404456,0.00003140874,0.00001763293],"domain_scores_gemma":[0.9999412,0.00001907948,0.000004222151,0.000005064388,0.00002077205,0.000009679673],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003814755,0.00009479028,0.006187647,0.000233655,0.00006089979,0.0004076792,0.00008270547,0.002196457,0.04376448,0.0001765688,0.03985615,0.9065576],"study_design_scores_gemma":[0.0001926372,0.001327065,0.4047003,0.0003683374,0.0003582538,0.009971369,0.001102721,0.3709577,0.1155927,0.003250233,0.09198356,0.0001951946],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5013162,0.01046456,0.3828971,0.0005860403,0.00130346,0.0007997234,0.05538013,0.02071747,0.02653538],"genre_scores_gemma":[0.4952683,0.005925973,0.4007526,0.0004324592,0.000466746,0.0005158877,0.05433564,0.0007936256,0.04150878],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00725987,"threshold_uncertainty_score":0.02051049,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02781559003690092,"score_gpt":0.3208766964766852,"score_spread":0.2930611064397842,"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."}}