{"id":"W3025743099","doi":"10.1109/vrw50115.2020.00193","title":"Perceptual Distortions Between Windows and Screens: Stereopsis Predicts Motion Parallax","year":2020,"lang":"en","type":"article","venue":"2020 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; York University","funders":"","keywords":"Parallax; Stereopsis; Computer science; Computer vision; Artificial intelligence; Perception; Binocular disparity; Computer graphics (images); Psychology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000249398,0.0003761436,0.0004265381,0.00005859273,0.0004333981,0.000566051,0.0002153084,0.0002577025,0.0002545374],"category_scores_gemma":[0.000304311,0.0003280724,0.00004781906,0.0001748092,0.0004226371,0.0005576277,0.0001275696,0.0006038731,0.00004908782],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002318873,"about_ca_system_score_gemma":0.00004671698,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006823005,"about_ca_topic_score_gemma":0.00007301155,"domain_scores_codex":[0.9976026,0.0001982203,0.0005182569,0.0009284983,0.0003799795,0.0003723835],"domain_scores_gemma":[0.9987086,0.0002467737,0.0002019289,0.000203313,0.00006701879,0.0005723418],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002140626,0.0007074451,0.004730737,0.0006537699,0.0001572095,0.00009221936,0.04231453,0.001506469,0.1865019,0.008247934,0.007264732,0.7456825],"study_design_scores_gemma":[0.01302587,0.0169271,0.6655557,0.004461041,0.001096841,0.0002222899,0.0414937,0.09258072,0.1204284,0.006536629,0.02991611,0.007755554],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9883654,0.00005001546,0.0043704,0.005012729,0.000184215,0.00032575,0.0002500151,0.0001460878,0.001295383],"genre_scores_gemma":[0.9963247,0.0008970692,0.00007075295,0.002001656,0.0002228882,0.00001423504,0.00002847894,0.0000256434,0.0004145693],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7379269,"threshold_uncertainty_score":0.9999171,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1416196306828466,"score_gpt":0.3281195891512365,"score_spread":0.1864999584683899,"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."}}