{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002675226,0.000178336,0.000135903,0.0001926273,0.0004635922,0.0002131504,0.0008669273,0.0001618111,0.0003226385],"category_scores_gemma":[0.00001427921,0.0001786183,0.00008393974,0.0004480088,0.00006380048,0.0003949087,0.00002154326,0.0005244887,0.0006357502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007232604,"about_ca_system_score_gemma":0.00004801825,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004622919,"about_ca_topic_score_gemma":0.0001075037,"domain_scores_codex":[0.998657,0.00002457531,0.0002395928,0.0004621501,0.0003146836,0.0003019647],"domain_scores_gemma":[0.9984124,0.00009883412,0.00006848372,0.001253064,0.000044846,0.0001223812],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00001212176,0.0001162815,0.000003849581,0.000002662151,0.000007576194,4.228054e-7,0.001140988,0.0002799423,0.1514854,0.04975689,0.00006447841,0.7971293],"study_design_scores_gemma":[0.009755033,0.003152397,0.3432917,0.0002680267,0.0003851739,0.0005298895,0.01068837,0.1903074,0.08039605,0.2238875,0.1288343,0.008504166],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1438666,4.651616e-7,0.8435998,0.0007820133,0.000292528,0.0002214859,0.000006003973,0.0003802931,0.01085086],"genre_scores_gemma":[0.9416923,0.00002510629,0.05742394,0.0004742893,0.000103844,0.00009883455,0.000007596971,0.00001723122,0.0001568484],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7978258,"threshold_uncertainty_score":0.8171495,"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."}}