{"id":"W2896231258","doi":"10.1016/j.gaitpost.2018.10.004","title":"Locomotor circumvention strategies in response to static pedestrians in a virtual and physical environment","year":2018,"lang":"en","type":"article","venue":"Gait & Posture","topic":"Virtual Reality Applications and Impacts","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"Jewish Rehabilitation Hospital; McGill University","funders":"","keywords":"Obstacle; Pedestrian; Task (project management); Computer science; Physical medicine and rehabilitation; Avatar; Virtual reality; Simulation; Gait; Virtual machine; Human–computer interaction; Adaptation (eye); Kinematics; Obstacle avoidance; Collision; Preferred walking speed; Psychology; Computer security; Artificial intelligence; Medicine; Engineering; Neuroscience; Transport engineering; Robot","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":[0.0002381717,0.0002888189,0.0004055881,0.000472685,0.0002267444,0.0004428606,0.0002178938,0.0004344809,0.001986003],"category_scores_gemma":[0.002050833,0.0002610673,0.0001624798,0.0001887814,0.0002112669,0.0001390782,0.0006815542,0.0002629671,0.0002664741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001476106,"about_ca_system_score_gemma":0.0002810332,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00202177,"about_ca_topic_score_gemma":0.00275058,"domain_scores_codex":[0.9998232,0.00005013168,0.00001226745,0.00002934385,0.00003095825,0.00005413046],"domain_scores_gemma":[0.9997255,0.00008015082,0.00004894468,0.0000235707,0.00004971583,0.000072078],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.009212654,0.000953772,0.07954565,0.0003393551,0.0003045669,0.00122989,0.003059627,0.01333373,0.8077267,0.0007376206,0.001659976,0.08189633],"study_design_scores_gemma":[0.0001654245,0.00514384,0.9357036,0.00009254471,0.0001495096,0.0009404297,0.002026077,0.03915278,0.01388561,0.0008166457,0.001865507,0.00005806834],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998323,0.00003024844,0.0007438764,0.00002270918,0.00001299344,0.00001630862,0.00006581316,0.00001789495,0.0007671372],"genre_scores_gemma":[0.9986449,0.00003028106,0.0005349697,0.0000258837,0.000003528789,0.00002188326,0.00007582681,0.000007459625,0.0006552367],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00202177,"threshold_uncertainty_score":0.006643832,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01240216011141768,"score_gpt":0.2758356404558207,"score_spread":0.2634334803444029,"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."}}