{"id":"W4402912291","doi":"10.1167/jov.24.10.993","title":"N170 and N250 sensitivity to diagnostic facial information during whole-face recognition","year":2024,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Face recognition and analysis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Face (sociological concept); Sensitivity (control systems); Facial recognition system; Artificial intelligence; Computer science; Pattern recognition (psychology); Engineering; Linguistics; Philosophy","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":[0.0005794501,0.0004611256,0.0003054473,0.000395284,0.0001761481,0.000286963,0.0002799402,0.0004360219,0.005184575],"category_scores_gemma":[0.002179508,0.0001367957,0.0002223281,0.0001849148,0.0002173228,0.0004263257,0.0005285859,0.0003876433,0.0006793756],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001799964,"about_ca_system_score_gemma":0.000136797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005845106,"about_ca_topic_score_gemma":0.001353385,"domain_scores_codex":[0.9998159,0.0000231219,0.00001049217,0.00005286627,0.00007659896,0.0000210182],"domain_scores_gemma":[0.9995512,0.000210889,0.00005593786,0.00004736057,0.00009748928,0.00003719253],"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":[0.001001439,0.00008698458,0.005414474,0.0002844476,0.00003089913,0.0003719616,0.0003700329,0.0004028382,0.9406282,0.000448633,0.001336799,0.04962331],"study_design_scores_gemma":[0.0001055824,0.001838373,0.6514817,0.00009141879,0.0001080619,0.004378761,0.0003341487,0.00883824,0.3173417,0.004794186,0.01058488,0.0001029022],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9749081,0.0007920727,0.01599089,0.0001650791,0.000191883,0.0001315112,0.001044763,0.0002740177,0.00650186],"genre_scores_gemma":[0.9822916,0.0003046724,0.01262219,0.0001770987,0.0001410312,0.0001481115,0.001201866,0.0001620711,0.002951501],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005184575,"threshold_uncertainty_score":0.01734406,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009445116193350794,"score_gpt":0.2552765547033836,"score_spread":0.2458314385100328,"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."}}