{"id":"W2063171660","doi":"10.1167/5.8.821","title":"Upright & inverted face recognition relies on the same, narrow band of spatial frequencies","year":2005,"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":"McMaster University","funders":"","keywords":"Spatial frequency; Facial recognition system; Face (sociological concept); Artificial intelligence; Pattern recognition (psychology); Frequency domain; Masking (illustration); Computer science; Orientation (vector space); Psychology; Computer vision; Speech recognition; Communication; Mathematics; Physics; Optics; 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":[0.0003838632,0.0003736339,0.0004856687,0.0005429884,0.0002445534,0.0009054405,0.0004199012,0.0005198516,0.005448471],"category_scores_gemma":[0.002289613,0.0002186265,0.0002873594,0.0001862915,0.0007068123,0.001325575,0.0007777424,0.0006046284,0.001087086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004411236,"about_ca_system_score_gemma":0.0003061196,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001591831,"about_ca_topic_score_gemma":0.001225612,"domain_scores_codex":[0.9994208,0.0000316704,0.00003870876,0.0001774883,0.0002280419,0.0001033071],"domain_scores_gemma":[0.9990169,0.0002295247,0.0002378186,0.000192233,0.0001868719,0.0001366113],"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":[0.0009088767,0.00008793011,0.01828056,0.0001267237,0.00003101245,0.0003430545,0.0001582064,0.0001875372,0.9282207,0.001360613,0.0005279644,0.04976685],"study_design_scores_gemma":[0.00006058376,0.0009530722,0.6413376,0.00005801963,0.00008160595,0.003194858,0.0005205523,0.008962221,0.3335933,0.007294524,0.003862933,0.00008083017],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9757645,0.0005228235,0.00973443,0.0001928632,0.0001045723,0.00004409134,0.0002693547,0.0000847433,0.01328276],"genre_scores_gemma":[0.9924182,0.0001761933,0.004749091,0.0002503629,0.00003289663,0.00002699709,0.0003111801,0.00003767886,0.001997487],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005448471,"threshold_uncertainty_score":0.01822692,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02951843520879922,"score_gpt":0.2654165508023322,"score_spread":0.235898115593533,"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."}}