{"id":"W4318605741","doi":"10.1109/aivr56993.2022.00012","title":"Improving Accessibility of Elevation Control in an Immersive Virtual Environment","year":2022,"lang":"en","type":"article","venue":"","topic":"Virtual Reality Applications and Impacts","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Wheelchair; Human–computer interaction; Computer science; Software; Multimedia; Virtual reality; Focus (optics); Focus group; Control (management); World Wide Web; Artificial intelligence; Operating system","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":[0.0004833588,0.00005306138,0.00009089534,0.00006997184,0.00007784483,0.00002521109,0.0004813098,0.00001475277,0.00009872116],"category_scores_gemma":[0.00001989284,0.00005184287,0.00002221274,0.0002037537,0.00002150162,0.000519369,0.0002256603,0.00008123194,0.000002916538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001378998,"about_ca_system_score_gemma":0.00005642975,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003236712,"about_ca_topic_score_gemma":0.00001680863,"domain_scores_codex":[0.9991025,0.0001002817,0.0002148471,0.0002395843,0.0002211689,0.0001216551],"domain_scores_gemma":[0.999357,0.00005303561,0.0001063778,0.0004211064,0.00001517849,0.00004728296],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000747247,0.001480107,0.01897661,0.00001226326,0.0000146213,0.000002345724,0.003475424,0.01777445,0.3870572,0.2289493,0.00008226607,0.3421007],"study_design_scores_gemma":[0.001231496,0.0009385237,0.1896105,0.000001574623,0.000004374174,0.000001766152,0.001308728,0.7932854,0.009720467,0.003368319,0.0003375704,0.0001913383],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4373197,0.000004895416,0.5620244,0.0002854849,0.00001685636,0.0001621685,0.000006409173,0.00000877549,0.000171364],"genre_scores_gemma":[0.9980675,0.000001068779,0.001539848,0.0003002766,0.000005187164,0.00005106943,0.000005274442,0.000002224745,0.00002752598],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7755109,"threshold_uncertainty_score":0.2114091,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01600211379996642,"score_gpt":0.2574651645195365,"score_spread":0.2414630507195701,"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."}}