{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006560567,0.0002731534,0.0002657631,0.0008717871,0.0002509113,0.001471064,0.000511662,0.0008490502,0.003218703],"category_scores_gemma":[0.005335466,0.0002155355,0.0002407126,0.0008679463,0.001934001,0.003071859,0.0005990489,0.0009307714,0.0004715428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002702598,"about_ca_system_score_gemma":0.0002666901,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007402608,"about_ca_topic_score_gemma":0.0005748429,"domain_scores_codex":[0.9998306,0.00002625007,0.00001672574,0.00005676849,0.00004529269,0.00002435908],"domain_scores_gemma":[0.9985361,0.0007960442,0.0001765087,0.0002140561,0.0002199272,0.00005725841],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0007680099,0.000412718,0.06739487,0.0009765128,0.000273925,0.0009910128,0.002167352,0.002088689,0.3575381,0.1082484,0.003340483,0.4557998],"study_design_scores_gemma":[0.00006411833,0.0003147917,0.5746698,0.0003463699,0.0001157345,0.003292801,0.001426874,0.003008954,0.02676722,0.3763069,0.01357412,0.0001124518],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8118763,0.03545288,0.1023665,0.006913706,0.0006614372,0.0001010541,0.0008062209,0.0002011403,0.04162072],"genre_scores_gemma":[0.9788578,0.006654962,0.01023856,0.0008049087,0.0005453411,0.00004061005,0.0001972864,0.0000395248,0.0026211],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003218703,"threshold_uncertainty_score":0.01076764,"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."}}