{"id":"W2990812265","doi":"10.1177/1071181319631216","title":"Introducing the VIMSSQ: Measuring susceptibility to visually induced motion sickness","year":2019,"lang":"en","type":"article","venue":"Proceedings of the Human Factors and Ergonomics Society Annual Meeting","topic":"Virtual Reality Applications and Impacts","field":"Computer Science","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Toronto; Toronto Rehabilitation Institute","funders":"","keywords":"Motion sickness; Nausea; Motion (physics); Task (project management); Psychology; Medicine; Physical medicine and rehabilitation; Computer science; Artificial intelligence; Psychiatry; Anesthesia; Engineering","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":[0.001350807,0.0001805703,0.0002235659,0.00002858205,0.000625441,0.0002809971,0.000961658,0.00008142857,0.000001814692],"category_scores_gemma":[0.0001831724,0.0001159835,0.0001517329,0.0003071325,0.00006891361,0.0006272136,0.0008511618,0.0002518401,0.000002639955],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001205732,"about_ca_system_score_gemma":0.00003199665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002393116,"about_ca_topic_score_gemma":0.000015104,"domain_scores_codex":[0.9986656,0.00001589881,0.0003427051,0.000446979,0.000230061,0.0002987884],"domain_scores_gemma":[0.9989417,0.0000936612,0.0002882491,0.0003062886,0.0002755372,0.00009458174],"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":[0.00002804492,0.0001678508,0.1060841,0.0003011431,0.0001134256,1.46209e-8,0.1084137,0.00069842,0.7225335,0.05191546,0.0006511186,0.009093197],"study_design_scores_gemma":[0.0007145209,0.0004098718,0.7442632,0.0003678455,0.00005906481,0.000004346964,0.03518353,0.01340358,0.1974595,0.006586264,0.000617179,0.0009310369],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976447,0.00001058318,0.0006540564,0.0007514752,0.0001328151,0.000425774,0.000004567033,0.00005075206,0.0003253101],"genre_scores_gemma":[0.9985603,0.000005111193,0.001111332,0.0001773661,0.00008904505,0.000008392617,6.069925e-7,0.00001244914,0.00003539995],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6381791,"threshold_uncertainty_score":0.4810449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02237479383853377,"score_gpt":0.2480314361773281,"score_spread":0.2256566423387944,"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."}}