{"id":"W3108922792","doi":"10.3389/frvir.2020.582095","title":"Visually Induced Motion Sickness on the Horizon","year":2020,"lang":"en","type":"article","venue":"Frontiers in Virtual Reality","topic":"Virtual Reality Applications and Impacts","field":"Computer Science","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Rehabilitation Institute; Toronto Metropolitan University; University Health Network","funders":"","keywords":"Motion sickness; Observer (physics); Motion (physics); Fixation (population genetics); Computer vision; Computer science; Simulation; Geodesy; Artificial intelligence; Communication; Psychology; Physical medicine and rehabilitation; Medicine; Geology; Physics","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":[0.0007459992,0.0001874277,0.0002414381,0.000074396,0.0001603489,0.0001693479,0.001182283,0.0001162616,0.00000822022],"category_scores_gemma":[0.0006125575,0.0001409588,0.0000744005,0.0009660796,0.00007276506,0.000408168,0.0002138312,0.0003808585,0.0000585534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001430595,"about_ca_system_score_gemma":0.0001014024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001213131,"about_ca_topic_score_gemma":0.00001257952,"domain_scores_codex":[0.998039,0.0003001752,0.0003404594,0.0005231444,0.0004622451,0.0003349977],"domain_scores_gemma":[0.9987072,0.0001420758,0.0001242659,0.0007527896,0.00006088117,0.0002127952],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009004294,0.0002770977,0.0005023142,0.00001370081,0.0000282432,0.000007436777,0.002917111,0.0005865425,0.001519747,0.5219585,0.04034838,0.4317509],"study_design_scores_gemma":[0.002889643,0.00573788,0.0974941,0.0001438535,0.00003870682,0.000007716777,0.003466003,0.7309536,0.01876647,0.08866543,0.04990202,0.001934604],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1028624,0.00001315691,0.8671337,0.02454198,0.0004022687,0.0004231393,0.00001286067,0.0001510808,0.004459417],"genre_scores_gemma":[0.9956904,0.000016013,0.0010009,0.003082588,0.000116386,0.00004477406,0.000009253026,0.00001115352,0.00002851814],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.892828,"threshold_uncertainty_score":0.5748134,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05482295349495828,"score_gpt":0.2846583756255953,"score_spread":0.229835422130637,"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."}}