{"id":"W3199677408","doi":"10.32393/csme.2021.223","title":"Manual Wheelchair Stroke Time Estimation Using Hand-Mounted Sensor","year":2021,"lang":"en","type":"article","venue":"Progress in Canadian Mechanical Engineering. Volume 4","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Wheelchair; Computer science; Estimation; Stroke (engine); Manual wheelchair; Physical medicine and rehabilitation; Artificial intelligence; Medicine; Engineering; World Wide Web; Mechanical engineering","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":[0.0001040662,0.0005622751,0.0004583673,0.001144474,0.0001120794,0.0003004273,0.000355631,0.0004411926,0.001092908],"category_scores_gemma":[0.0005415724,0.0001403568,0.0002400931,0.0006915201,0.00006267983,0.0003276743,0.0002099836,0.0001413813,0.0004472924],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000125827,"about_ca_system_score_gemma":0.0002047816,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001900924,"about_ca_topic_score_gemma":0.002184232,"domain_scores_codex":[0.9998074,0.00002130951,0.00001658523,0.00005637388,0.00007719496,0.00002112225],"domain_scores_gemma":[0.999845,0.00002599555,0.00003463055,0.00001062276,0.00007266378,0.00001098743],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001142049,0.0003400436,0.0582613,0.0008716222,0.0002579459,0.0006801416,0.0002485267,0.03093458,0.2078858,0.0006687262,0.004261546,0.6944478],"study_design_scores_gemma":[0.00008126658,0.0009924667,0.2282998,0.0001279716,0.000212885,0.001387503,0.0003217098,0.6874332,0.07386128,0.0006541899,0.006495067,0.0001327037],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6116731,0.002252564,0.3742177,0.00009697387,0.0002562398,0.0002156991,0.001455216,0.002442469,0.007389977],"genre_scores_gemma":[0.9546362,0.0008354677,0.04158647,0.00005070532,0.00005709119,0.0001602797,0.0005415938,0.00002157715,0.002110614],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001900924,"threshold_uncertainty_score":0.003779709,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008434859307545336,"score_gpt":0.2465143307208187,"score_spread":0.2380794714132734,"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."}}