{"id":"W4247310578","doi":"10.21203/rs.3.rs-86713/v1","title":"Augmented Feedback for Manual Wheelchair Propulsion Technique Training in a Virtual Reality Simulator","year":2020,"lang":"en","type":"preprint","venue":"Research Square","topic":"Virtual Reality Applications and Impacts","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"AGE-WELL","keywords":"Wheelchair; Virtual reality; Simulation; Computer science; Propulsion; Training (meteorology); Manual wheelchair; Flight simulator; Human–computer interaction; Aeronautics; Physical medicine and rehabilitation; Engineering; Aerospace engineering; Medicine; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003980425,0.0003612904,0.0005780496,0.0005975678,0.000291619,0.0004978561,0.002190715,0.0005297693,0.00001197472],"category_scores_gemma":[0.001474275,0.0003485534,0.0002118215,0.001260802,0.000154365,0.0003297738,0.003064717,0.001934048,0.00003343817],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007151599,"about_ca_system_score_gemma":0.001617037,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004640282,"about_ca_topic_score_gemma":0.0001511988,"domain_scores_codex":[0.9947845,0.0006974288,0.0006909442,0.001454805,0.001339641,0.001032662],"domain_scores_gemma":[0.9965504,0.0006148994,0.0001813061,0.001561849,0.000596708,0.0004948489],"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":[0.0009544356,0.001739645,0.0002285854,0.005767668,0.0001794129,0.0001374149,0.03050062,0.02015731,0.01870825,0.3356588,0.01981254,0.5661553],"study_design_scores_gemma":[0.001973958,0.002472247,0.003627928,0.002803063,0.00001174819,0.00001123006,0.002394531,0.7595371,0.007345264,0.1907673,0.02781241,0.001243252],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00973619,0.00007617778,0.9656255,0.01409701,0.0001385069,0.008697032,0.0003945013,0.0003886138,0.0008465105],"genre_scores_gemma":[0.9854287,0.00005589224,0.01018072,0.0001151175,0.0002293491,0.003544986,0.0002359566,0.00004530074,0.000163996],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9756925,"threshold_uncertainty_score":0.9998966,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.179641503274252,"score_gpt":0.4495415379794082,"score_spread":0.2699000347051562,"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."}}