{"id":"W4386244525","doi":"10.1167/jov.23.9.5140","title":"Stereoscopic slant contrast revisited","year":2023,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Contrast (vision); Stereoscopy; Stereopsis; Mathematics; Surface (topology); Matching (statistics); Geometry; Optics; Physics; Statistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002318701,0.0002147573,0.0002920784,0.0005933009,0.0001704858,0.0006208778,0.0003931727,0.0003794073,0.002479999],"category_scores_gemma":[0.002500246,0.0001344936,0.0002422785,0.0003915406,0.0007283846,0.0008137937,0.0008902128,0.0008681567,0.000205215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000273269,"about_ca_system_score_gemma":0.000144444,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00055081,"about_ca_topic_score_gemma":0.0005181511,"domain_scores_codex":[0.9996364,0.0000377733,0.00001480401,0.00006901954,0.0001878577,0.00005416305],"domain_scores_gemma":[0.9992429,0.0003164368,0.0001545675,0.0001174046,0.0001204485,0.00004823435],"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":[0.001151248,0.00005830321,0.01672994,0.0003331789,0.00006146956,0.0009181903,0.0006209798,0.002572783,0.8561979,0.03352787,0.0009338838,0.08689431],"study_design_scores_gemma":[0.0001216398,0.0008407444,0.4561768,0.000139454,0.0001521478,0.007094261,0.0008694263,0.02941018,0.4215904,0.06481592,0.01864368,0.0001452981],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9402884,0.001676655,0.02296703,0.0002635062,0.0001202741,0.00002228482,0.0001427059,0.000202048,0.03431716],"genre_scores_gemma":[0.9977696,0.0001402171,0.001383236,0.00004460344,0.00001799033,0.000003817986,0.00003891776,0.00002511498,0.0005764995],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002479999,"threshold_uncertainty_score":0.00829643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0660640898664027,"score_gpt":0.3743077367722581,"score_spread":0.3082436469058554,"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."}}