{"id":"W3197320194","doi":"10.1167/jov.21.9.2266","title":"Local Symmetry in Human and Artificial Neural Networks","year":2021,"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":"University of Toronto","funders":"","keywords":"Convolutional neural network; Categorization; Symmetry (geometry); Computer science; Perception; Artificial intelligence; Similarity (geometry); Pattern recognition (psychology); Visual perception; Visual cortex; Human visual system model; Psychology; Mathematics; Neuroscience; Image (mathematics); 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":[0.001781965,0.0005248254,0.0005002288,0.001167031,0.0002510687,0.001433187,0.0006578803,0.0007818532,0.001732032],"category_scores_gemma":[0.007317942,0.0002951369,0.0004246621,0.0009903008,0.001464758,0.001669542,0.001026388,0.0008287778,0.0002681482],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009231762,"about_ca_system_score_gemma":0.0004155092,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004678495,"about_ca_topic_score_gemma":0.002453306,"domain_scores_codex":[0.9991271,0.0003195697,0.00004214751,0.0002998226,0.0001586392,0.00005268032],"domain_scores_gemma":[0.9985273,0.0007754708,0.0002837102,0.0002185967,0.0001421363,0.00005279974],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0001633291,0.00007088062,0.01459126,0.0005008496,0.0003812144,0.0002471021,0.0004036188,0.5127131,0.005625887,0.2217717,0.007296944,0.2362342],"study_design_scores_gemma":[0.0000105538,0.00003978064,0.007842434,0.00005673327,0.00002177954,0.0001157152,0.00005702456,0.7462046,0.001183782,0.2403327,0.004105074,0.0000298165],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2028745,0.01418532,0.7552673,0.004348913,0.0004406852,0.00008400012,0.001446058,0.001412102,0.01994121],"genre_scores_gemma":[0.926696,0.002691515,0.06635584,0.0002860585,0.000207451,0.00008712943,0.0006529699,0.00008639922,0.002936636],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004678495,"threshold_uncertainty_score":0.00942409,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05227954144600781,"score_gpt":0.3620682793679618,"score_spread":0.3097887379219539,"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."}}