{"id":"W2000099809","doi":"10.1068/p5584","title":"Effects of Image Background on Spatial-Frequency Thresholds for Face Recognition","year":2006,"lang":"en","type":"article","venue":"Perception","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Spatial frequency; Luminance; Stimulus (psychology); Artificial intelligence; Psychophysics; Pattern recognition (psychology); Facial recognition system; Computer science; Computer vision; Filter (signal processing); Spatial filter; Set (abstract data type); Cognitive neuroscience of visual object recognition; Visual processing; Mathematics; Communication; Psychology; Perception; Object (grammar); Cognitive psychology; Optics; Physics","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":[0.0005169878,0.0002853775,0.000283174,0.0003817415,0.0001227982,0.0004210951,0.0003375238,0.0003428665,0.002343048],"category_scores_gemma":[0.005239714,0.0002724989,0.0001853931,0.0001420564,0.0004512175,0.0004977363,0.0003923938,0.0003992493,0.000311333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004027543,"about_ca_system_score_gemma":0.0001496805,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006992699,"about_ca_topic_score_gemma":0.0005864473,"domain_scores_codex":[0.9995745,0.0001061784,0.00004035934,0.00008804571,0.0001239692,0.00006697705],"domain_scores_gemma":[0.9973864,0.001941443,0.0001786925,0.0001817724,0.0001619248,0.000149776],"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":[0.0007458132,0.00004906711,0.002009983,0.00006474715,0.00001321772,0.00006239852,0.00004667704,0.0004188198,0.9900436,0.0001883631,0.00003122335,0.006326059],"study_design_scores_gemma":[0.00006182039,0.001501934,0.1790283,0.00003182866,0.0000712832,0.0005736095,0.00006982864,0.006964392,0.810348,0.0007772238,0.0005421175,0.00002968309],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9895331,0.0005651154,0.00768543,0.00005843765,0.00001818805,0.00002999893,0.00005619486,0.00007071711,0.001982817],"genre_scores_gemma":[0.9952018,0.0002061579,0.003997765,0.00007930618,0.000006163036,0.00002164171,0.00007982262,0.00004891288,0.000358437],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002343048,"threshold_uncertainty_score":0.007838309,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04371094811736791,"score_gpt":0.2937706958838451,"score_spread":0.2500597477664772,"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."}}