{"id":"W2579569765","doi":"10.1123/jab.2016-0143","title":"Inverse Dynamics Modeling of Paralympic Wheelchair Curling","year":2017,"lang":"en","type":"article","venue":"Journal of Applied Biomechanics","topic":"Spinal Cord Injury Research","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Curling; Kinematics; Inverse dynamics; Wheelchair; Biomechanics; Inverse kinematics; Physical medicine and rehabilitation; Angular velocity; Elbow; Simulation; Computer science; Engineering; Medicine; Physics; Mechanical engineering; Anatomy","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":[0.0001871493,0.0004188907,0.0004234096,0.0003487505,0.0003179065,0.0006321326,0.000515005,0.0006767713,0.001769031],"category_scores_gemma":[0.0004746671,0.0003223507,0.000375044,0.0001938176,0.0003718625,0.0002695691,0.0004738385,0.00027256,0.0003664851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003243128,"about_ca_system_score_gemma":0.0007770105,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01820201,"about_ca_topic_score_gemma":0.01143298,"domain_scores_codex":[0.9999118,0.00001619898,0.000005138631,0.00001938694,0.00003409082,0.00001343066],"domain_scores_gemma":[0.9998906,0.00004050496,0.00002643487,0.00000866596,0.00002576566,0.0000080413],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003711681,0.00002381182,0.0008667097,0.0000478278,0.00001443489,0.0001348021,0.00009411779,0.9838847,0.006408462,0.00145994,0.0001575656,0.006870436],"study_design_scores_gemma":[0.000002570113,0.00001158029,0.0003378342,0.000002987651,0.000002943442,0.00001281908,0.00001452914,0.9987215,0.0004136309,0.0002064148,0.0002700609,0.000003073398],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3046027,0.0003211422,0.6794696,0.0002385179,0.00003972104,0.0001194366,0.0003134688,0.0005249494,0.01437048],"genre_scores_gemma":[0.9783692,0.0001831474,0.01660487,0.00002316687,0.000005052137,0.0000912108,0.0001152778,0.00003938112,0.004568635],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01820201,"threshold_uncertainty_score":0.03619212,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0580615339590017,"score_gpt":0.3586216163520782,"score_spread":0.3005600823930765,"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."}}