{"id":"W1974636366","doi":"10.1167/8.16.3","title":"Depth estimation from retinal disparity requires eye and head orientation signals","year":2008,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; York University; Research Canada; Canadian Institutes of Health Research","funders":"","keywords":"Orientation (vector space); Computer vision; Artificial intelligence; Computer science; Head (geology); Point (geometry); Binocular disparity; Eye movement; Object (grammar); Binocular vision; Mathematics; Geology; Geometry","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":[0.0003550129,0.000318516,0.0004110131,0.0002149623,0.0001581549,0.0007230751,0.0002448958,0.0003670669,0.0005508912],"category_scores_gemma":[0.002393794,0.0003653582,0.0004084081,0.0001855637,0.0004736662,0.001011344,0.0006820373,0.0004684169,0.0001124479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005106518,"about_ca_system_score_gemma":0.0007089806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003279892,"about_ca_topic_score_gemma":0.002546562,"domain_scores_codex":[0.99978,0.00004292223,0.000009726024,0.00005895799,0.00007177722,0.00003659204],"domain_scores_gemma":[0.9995556,0.0002079721,0.00008894513,0.0000535246,0.00006091983,0.00003309268],"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":[0.0005597831,0.00007172531,0.02056958,0.0002293823,0.0001189003,0.0003236539,0.0003020029,0.1512198,0.7401667,0.02331488,0.0003049599,0.06281859],"study_design_scores_gemma":[0.00005889875,0.0005107893,0.1008276,0.00004213714,0.0000903535,0.0006551413,0.000134811,0.7569476,0.1150246,0.02478881,0.0008039975,0.0001152488],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7587519,0.0002007313,0.2384305,0.0001477984,0.00001636988,0.00002097079,0.0001272792,0.0001528467,0.002151513],"genre_scores_gemma":[0.9865777,0.0001286313,0.01290691,0.00001855075,0.000004864443,0.000008902073,0.00006462357,0.0000130625,0.0002767384],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003279892,"threshold_uncertainty_score":0.006521583,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08012882447014345,"score_gpt":0.3943948623865978,"score_spread":0.3142660379164544,"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."}}