{"id":"W2051882706","doi":"10.1167/10.1.9","title":"A biologically plausible model of human shape symmetry perception","year":2010,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; Université de Montréal","funders":"","keywords":"Symmetry (geometry); Object (grammar); ENCODE; Curvature; Concentric; Perception; Position (finance); Artificial intelligence; Computer vision; Computer science; Geometry; Topology (electrical circuits); Mathematics; Psychology; Combinatorics","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":[0.0002307079,0.0003802688,0.0003574333,0.0002947505,0.0003039128,0.0009593469,0.00116295,0.001334539,0.005415323],"category_scores_gemma":[0.0007449385,0.0003035933,0.0007489113,0.0001673665,0.0008062261,0.001714176,0.0004971289,0.0006701001,0.001641674],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004450453,"about_ca_system_score_gemma":0.0004686784,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001254785,"about_ca_topic_score_gemma":0.0007359943,"domain_scores_codex":[0.9998746,0.00002188489,0.000003534192,0.00005164431,0.00003219378,0.00001612226],"domain_scores_gemma":[0.9998896,0.0000300306,0.00001405796,0.00002727109,0.00002198054,0.00001702089],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002553413,0.0001492266,0.002806905,0.0002948067,0.000143295,0.0007725138,0.0005708526,0.2221033,0.1053358,0.5549861,0.00874076,0.1038411],"study_design_scores_gemma":[0.00004387287,0.0001470413,0.002648426,0.00002314976,0.00001940694,0.0007686055,0.00007320801,0.6569031,0.003606579,0.3314332,0.004290297,0.00004308239],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0914683,0.0007650444,0.8654712,0.003720437,0.0001931664,0.00008083018,0.0003839463,0.001064633,0.03685242],"genre_scores_gemma":[0.9050518,0.0004386336,0.08650398,0.0004268702,0.00007317102,0.0001054854,0.0002503221,0.00005674914,0.007093007],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005415323,"threshold_uncertainty_score":0.01811606,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08453616872276802,"score_gpt":0.3787688108894143,"score_spread":0.2942326421666463,"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."}}