{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002642595,0.000204493,0.0002654897,0.0003625947,0.00009385936,0.0001876844,0.0004966693,0.0002282371,0.00004749814],"category_scores_gemma":[0.000203227,0.0002427422,0.0000623751,0.0006275567,0.00004806845,0.0001993233,0.0001304842,0.0003838032,0.00007470851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004718032,"about_ca_system_score_gemma":0.0004150069,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003317501,"about_ca_topic_score_gemma":0.005972056,"domain_scores_codex":[0.9982087,0.00004175309,0.0002817099,0.0005000756,0.0002255573,0.0007422253],"domain_scores_gemma":[0.9989884,0.00004091494,0.00004961307,0.0004580359,0.0001104651,0.0003525854],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003251579,0.0006584076,0.01836487,0.0004881425,0.0003875301,0.01022507,0.0007237573,0.1199019,0.03992105,0.2594015,0.001543258,0.548352],"study_design_scores_gemma":[0.0002461309,0.00003503253,0.002212299,0.00007344208,0.000006874181,0.0001169801,0.000005576921,0.9901738,0.004153101,0.000220435,0.002494645,0.0002617433],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2440318,0.0008122799,0.7488003,0.004189415,0.0008851232,0.0003163946,0.00005838498,0.0008018348,0.0001044545],"genre_scores_gemma":[0.8477161,0.000001806439,0.1518886,0.00009218321,0.00004063148,0.00002066704,0.00001211908,0.00002370208,0.0002042151],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8702719,"threshold_uncertainty_score":0.9898738,"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."}}