{"id":"W2105167740","doi":"10.1145/1670671.1670675","title":"Making virtual walking real","year":2010,"lang":"en","type":"article","venue":"ACM Transactions on Applied Perception","topic":"Virtual Reality Applications and Impacts","field":"Computer Science","cited_by":69,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Sixth Framework Programme","keywords":"Treadmill; Preferred walking speed; Computer science; Simulation; Virtual reality; Power walking; Position (finance); Control (management); Motion (physics); Human–computer interaction; Physical medicine and rehabilitation; Computer vision; Artificial intelligence; Physical therapy","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":[0.001454677,0.00135693,0.0005392467,0.0006906261,0.0009145875,0.003504494,0.001807601,0.001302657,0.01961612],"category_scores_gemma":[0.007644586,0.0005863511,0.000625237,0.0003389917,0.00130448,0.004757606,0.005589067,0.001342009,0.004190901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003898552,"about_ca_system_score_gemma":0.0004032291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005828,"about_ca_topic_score_gemma":0.0008412192,"domain_scores_codex":[0.9985949,0.0005556054,0.00008862242,0.0002757098,0.0003333068,0.0001518932],"domain_scores_gemma":[0.9974868,0.0005724777,0.0001706758,0.0007658075,0.000531454,0.0004728537],"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":[0.001149797,0.000888893,0.004974625,0.001202548,0.000170551,0.00110636,0.008821519,0.01388257,0.07094616,0.1015283,0.07657897,0.7187498],"study_design_scores_gemma":[0.0003928179,0.001523301,0.008616417,0.0007299624,0.0003581195,0.001913754,0.006451278,0.03481346,0.02828229,0.08083405,0.835735,0.000349642],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1800207,0.001632719,0.6757353,0.004576537,0.004388957,0.0007781964,0.0007212517,0.008088517,0.1240577],"genre_scores_gemma":[0.7367213,0.001385595,0.2251325,0.001779669,0.0005637118,0.001080487,0.001223078,0.001286493,0.03082713],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01961612,"threshold_uncertainty_score":0.06562251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03591049351963052,"score_gpt":0.3057643680303102,"score_spread":0.2698538745106797,"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."}}