{"id":"W4367662791","doi":"10.1109/vr55154.2023.00055","title":"Manipulation of Motion Parallax Gain Distorts Perceived Distance and Object Depth in Virtual Reality","year":2023,"lang":"en","type":"article","venue":"","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Parallax; Monocular; Depth perception; Computer vision; Binocular disparity; Artificial intelligence; Computer science; Virtual reality; Perception; Stereopsis; Sensory cue; Illusion; Stereoscopy; Psychology; Cognitive psychology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000416481,0.0005138044,0.0002798399,0.0002693297,0.0001364008,0.0005230747,0.0003417686,0.0003306602,0.001073544],"category_scores_gemma":[0.00391847,0.0003224411,0.0002414226,0.0001249224,0.0004180116,0.0005714145,0.0009605085,0.0003548368,0.0001002737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000266423,"about_ca_system_score_gemma":0.0002083061,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001080244,"about_ca_topic_score_gemma":0.0008298371,"domain_scores_codex":[0.9994256,0.0001602434,0.00005006116,0.00008348601,0.0001808979,0.00009980491],"domain_scores_gemma":[0.9980993,0.00113704,0.0003880111,0.0001670422,0.00008619329,0.0001224682],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009675014,0.0000869696,0.001927158,0.0001381015,0.00002045392,0.00008029937,0.0002986208,0.003484105,0.9841152,0.0002576701,0.00002960118,0.008594348],"study_design_scores_gemma":[0.0002160743,0.005739094,0.1367941,0.00009440415,0.0001950844,0.0009593292,0.0007753978,0.05899514,0.7934625,0.0009999191,0.001621864,0.0001472347],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951665,0.00008632972,0.004404978,0.00001436361,0.000006015975,0.00001178737,0.00001528497,0.00002622463,0.0002684183],"genre_scores_gemma":[0.9973726,0.00007669783,0.002304106,0.00001301076,0.000002284509,0.00001093536,0.0000209289,0.00001026805,0.000189148],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001080244,"threshold_uncertainty_score":0.003591359,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09859355765442084,"score_gpt":0.3428887660174608,"score_spread":0.2442952083630399,"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."}}