{"id":"W2067148447","doi":"10.1167/14.2.14","title":"Interactions between cues to visual motion in depth","year":2014,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Looming; Computer vision; Binocular disparity; Observer (physics); Artificial intelligence; Stimulus (psychology); Kinetic depth effect; Relative motion; Depth perception; Motion (physics); Motion perception; Geology; Optics; Computer science; Binocular vision; Physics; Psychology; Neuroscience; Perception; Cognitive 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":[],"consensus_categories":[],"category_scores_codex":[0.000458439,0.00006357296,0.0001292121,0.0003076174,0.00006576597,0.00006403767,0.0001175201,0.00003363935,0.0000434958],"category_scores_gemma":[0.0005487146,0.00005120653,0.00004746402,0.0002475059,0.00001088713,0.0003740176,0.00002734712,0.0002034119,0.0001393662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004626013,"about_ca_system_score_gemma":0.00001371512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002806473,"about_ca_topic_score_gemma":0.000009288625,"domain_scores_codex":[0.9990707,0.0001529645,0.0003073512,0.0001084999,0.0002552595,0.0001052071],"domain_scores_gemma":[0.999518,0.000115775,0.0001560677,0.00005376696,0.00005492154,0.0001014634],"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":[0.00004187018,0.0001024157,0.001240984,0.000006161966,6.537442e-7,0.000002903463,0.0003781697,0.0001215244,0.7998657,0.00009397708,0.0003157656,0.1978299],"study_design_scores_gemma":[0.001666575,0.00409884,0.4266837,0.0008008327,0.00002441232,0.000158648,0.000381605,0.01018755,0.5272545,0.005707436,0.02264984,0.0003861264],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9466931,0.000002166026,0.05167075,0.0007862242,0.0004034169,0.00003777348,4.077625e-7,0.00002707016,0.0003791086],"genre_scores_gemma":[0.9982111,0.000006357724,0.0008154272,0.000606056,0.0002583477,4.551214e-7,2.168632e-7,0.00001336239,0.00008865185],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4254427,"threshold_uncertainty_score":0.2088142,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06716003737077104,"score_gpt":0.4146159916980778,"score_spread":0.3474559543273068,"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."}}