{"id":"W3101611305","doi":"10.1016/j.medengphy.2020.11.008","title":"A high sample rate, wireless instrumented wheel for measuring 3D pushrim kinetics of a racing wheelchair","year":2020,"lang":"en","type":"article","venue":"Medical Engineering & Physics","topic":"Spinal Cord Injury Research","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke; Centre for Interdisciplinary Research in Rehabilitation; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Wheelchair; Biomechanics; Simulation; Acceleration; Work (physics); Kinematics; Engineering; Force platform; Automotive engineering; Physical medicine and rehabilitation; Computer science; Mechanical engineering; Physics; Medicine","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":[0.0006266569,0.0005778543,0.0005383331,0.0009306228,0.0002418297,0.000565075,0.0005336832,0.0005125629,0.002846971],"category_scores_gemma":[0.001309582,0.0003375961,0.0002341323,0.000667589,0.0001862524,0.0004580008,0.0004526696,0.0002076157,0.0009319538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001524891,"about_ca_system_score_gemma":0.0006157678,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00123962,"about_ca_topic_score_gemma":0.002775045,"domain_scores_codex":[0.9994339,0.00008781808,0.00005006463,0.0001009362,0.0002875081,0.00003972903],"domain_scores_gemma":[0.9991789,0.0002219309,0.0001262794,0.00009625609,0.0003251799,0.00005138076],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007704105,0.0003171243,0.03065393,0.0005165124,0.00008966537,0.0002629354,0.0002462662,0.001268674,0.8077558,0.0003786548,0.002467983,0.1552721],"study_design_scores_gemma":[0.0001985339,0.003064428,0.1915692,0.0001911373,0.0004448162,0.002984943,0.0004755547,0.04428788,0.7253236,0.0004785861,0.03065866,0.0003228491],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4267863,0.0008201892,0.5618718,0.0002030664,0.0002858388,0.0008088911,0.002912825,0.00291549,0.00339565],"genre_scores_gemma":[0.6840776,0.0006721469,0.3075357,0.0002193735,0.00006754742,0.001103542,0.0009373894,0.000249897,0.005136807],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002846971,"threshold_uncertainty_score":0.009523988,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04142931131066875,"score_gpt":0.2922562919030411,"score_spread":0.2508269805923724,"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."}}