{"id":"W4386242619","doi":"10.1167/jov.23.9.5786","title":"Transformational Apparent Motion In A Recurrent Neural Network","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":"York University","funders":"","keywords":"Artificial intelligence; Stimulus (psychology); Discriminative model; Perception; Pattern recognition (psychology); Motion (physics); Computer science; Biological motion; Artificial neural network; Psychology; Computer vision; Cognitive 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005854258,0.0004675159,0.0004502827,0.0002091093,0.0001623366,0.0003740733,0.0006353738,0.0004164641,0.0004995934],"category_scores_gemma":[0.001393334,0.0003397411,0.0004803593,0.0001610928,0.0004327505,0.0004995738,0.0003997192,0.0005840022,0.0001094063],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006400128,"about_ca_system_score_gemma":0.0003346166,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005763956,"about_ca_topic_score_gemma":0.005005093,"domain_scores_codex":[0.9998198,0.00004815641,0.00000803247,0.00006224977,0.00002762599,0.0000341469],"domain_scores_gemma":[0.9996824,0.0001480502,0.00005010656,0.00003008795,0.00006496959,0.00002443839],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002485807,0.00009595264,0.002234809,0.00004984846,0.0000782232,0.0002115456,0.0001012557,0.9232599,0.03686243,0.002420831,0.0004778969,0.0339588],"study_design_scores_gemma":[0.000002361716,0.00001911817,0.0002401369,0.000001001321,0.000003441702,0.000005762715,0.000001853501,0.9986044,0.0008273128,0.0002667303,0.00002576982,0.0000020929],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7743991,0.0003125,0.22223,0.0003256771,0.00006539128,0.00004081006,0.0001232537,0.0006657314,0.00183749],"genre_scores_gemma":[0.9800251,0.00005969454,0.01862536,0.00003121645,0.000008036897,0.00002688361,0.0001162537,0.00001774873,0.001089755],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005763956,"threshold_uncertainty_score":0.01146078,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07725822876512098,"score_gpt":0.3704005569577866,"score_spread":0.2931423281926656,"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."}}