{"id":"W2067743397","doi":"10.1016/j.cogbrainres.2004.03.013","title":"Electrophysiological correlates of object categorization: back to basics","year":2004,"lang":"en","type":"article","venue":"Cognitive Brain Research","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":48,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University; Nova Scotia Hospital; Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Categorization; Superordinate goals; Psychology; Generality; Cognition; Cognitive psychology; Object (grammar); Contrast (vision); Communication; Neuroscience; Artificial intelligence; Computer science; Social psychology","routes":{"ca_aff":true,"ca_fund":true,"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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0005001449,0.0001119892,0.0001554599,0.0002525306,0.0001986344,0.00004322945,0.000190537,0.0001033195,0.001512487],"category_scores_gemma":[0.005878048,0.00009910017,0.00005981748,0.001323442,0.0003697436,0.0001148778,0.0001047758,0.0004034175,0.004187801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007630741,"about_ca_system_score_gemma":0.0001682175,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000180665,"about_ca_topic_score_gemma":0.000008621392,"domain_scores_codex":[0.9978476,0.0005467866,0.0001951958,0.0004356489,0.0005404451,0.0004343186],"domain_scores_gemma":[0.9977529,0.00140522,0.00003506036,0.0001231848,0.0005257702,0.0001578534],"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":[0.0003414396,0.0002314168,0.0002265484,0.00002771084,0.000004144727,0.00001494589,0.0006023361,0.00007006736,0.9827343,0.006163026,0.0005278097,0.009056265],"study_design_scores_gemma":[0.001311113,0.002344548,0.02391337,0.0001512715,0.000004718852,0.00002149259,0.0007392286,0.0001163551,0.9523456,0.01769641,0.001096218,0.0002597291],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9748306,0.00001407207,0.004539966,0.001721062,0.00008516622,0.0006829745,0.00004634836,0.00004368229,0.01803616],"genre_scores_gemma":[0.9976324,0.00008632347,0.0001091713,0.0009924476,0.00007668015,0.00004545216,0.00002997276,0.00001588242,0.001011668],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03038874,"threshold_uncertainty_score":0.9994003,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1625652276332807,"score_gpt":0.4077089172130156,"score_spread":0.245143689579735,"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."}}