{"id":"W1969577579","doi":"10.1068/p6252","title":"Perceptual Artifacts in Random-Dot Stereograms","year":2010,"lang":"en","type":"article","venue":"Perception","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Perception; Stereopsis; Computer vision; Depth perception; Artificial intelligence; Computer science; Optics; Physics; Psychology; Neuroscience","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003701684,0.0001773774,0.0001762633,0.0001876168,0.0001655493,0.0001374436,0.0002091546,0.0001601095,0.006589076],"category_scores_gemma":[0.0002954783,0.0001628526,0.00007530069,0.0003066095,0.0001271222,0.0004011881,0.00004271738,0.0005156787,0.002675471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003545297,"about_ca_system_score_gemma":0.00003579778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000422425,"about_ca_topic_score_gemma":0.0002204739,"domain_scores_codex":[0.9984308,0.000142706,0.0002786541,0.0004716448,0.0003218162,0.0003544011],"domain_scores_gemma":[0.9994699,0.00006407304,0.00006043775,0.0002427535,0.00002934857,0.0001334635],"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":[0.00007409632,0.0001114452,0.0006740722,0.000008894027,3.222511e-7,0.000004311378,0.002439883,0.000007294854,0.9341488,0.00023393,0.00007840025,0.06221851],"study_design_scores_gemma":[0.0151641,0.001083608,0.5387272,0.0001998315,0.00004873693,0.000500288,0.008136902,0.01986634,0.3716595,0.008078771,0.03370278,0.002831914],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9909717,0.000001074569,0.000922604,0.0003329598,0.0007616095,0.0002326095,0.000003318546,0.0001966305,0.006577514],"genre_scores_gemma":[0.9968624,0.00002010136,0.0005518072,0.001240685,0.0002106583,0.00003297238,0.000009033557,0.00002591884,0.001046396],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5624893,"threshold_uncertainty_score":0.9981011,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05531276154030471,"score_gpt":0.3253594049177512,"score_spread":0.2700466433774464,"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."}}