{"id":"W2115609306","doi":"10.1111/j.0956-7976.2004.00752.x","title":"Receptive Fields for Flexible Face Categorizations","year":2004,"lang":"en","type":"article","venue":"Psychological Science","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":96,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Categorization; Psychology; Cognitive psychology; Face (sociological concept); Task (project management); Face perception; Information processing; Communication; Neuroscience; Artificial intelligence; Perception; Computer science; Linguistics","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":[0.0003811031,0.000110043,0.0001460063,0.0004330369,0.00009912238,0.0004990945,0.0001933508,0.000281634,0.002909579],"category_scores_gemma":[0.002915305,0.0001232112,0.0001617551,0.000121583,0.000269304,0.0004049634,0.0002862735,0.0002641809,0.0002702895],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002236171,"about_ca_system_score_gemma":0.0001138724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003314287,"about_ca_topic_score_gemma":0.0002308716,"domain_scores_codex":[0.9998893,0.00002200973,0.000005075744,0.0000274852,0.00002696344,0.00002922658],"domain_scores_gemma":[0.9988874,0.0007447172,0.0001009161,0.00008129061,0.0001171166,0.00006859459],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002740772,0.00003411637,0.004783115,0.0000814728,0.00001455174,0.0001078138,0.0001070109,0.001875424,0.9564462,0.006592533,0.000360882,0.0293228],"study_design_scores_gemma":[0.0001608616,0.000396033,0.4607181,0.00008080255,0.00009206247,0.00311782,0.0004287442,0.137069,0.3204697,0.0736218,0.003744543,0.0001006389],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9281335,0.0004436808,0.06364845,0.0002099518,0.00002911213,0.00003659071,0.000284864,0.0002036125,0.007010162],"genre_scores_gemma":[0.996436,0.00004239107,0.003075504,0.00002221734,0.00001124063,0.00001508085,0.00006447563,0.00001455099,0.0003185728],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002909579,"threshold_uncertainty_score":0.009733498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1587889077586027,"score_gpt":0.4253037574809084,"score_spread":0.2665148497223057,"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."}}