{"id":"W2056115024","doi":"10.3758/app.72.6.1444","title":"Recognizing famous people","year":2010,"lang":"en","type":"article","venue":"Attention Perception & Psychophysics","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":53,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; University of Victoria","funders":"Canadian Institutes of Health Research; Université de Montréal; Fonds Québécois de la Recherche sur la Nature et les Technologies; James S. McDonnell Foundation","keywords":"Ranging; Task (project management); Face (sociological concept); Artificial intelligence; Context (archaeology); Computer science; Identification (biology); Set (abstract data type); Observer (physics); Replicate; Spatial contextual awareness; Computer vision; Pattern recognition (psychology); Psychology; Mathematics; Geography; Statistics","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":[0.0002311381,0.0003879463,0.0003686645,0.0003402357,0.0003699952,0.00122141,0.0004091306,0.0008736174,0.01069792],"category_scores_gemma":[0.001480929,0.000240455,0.0003866579,0.0002232873,0.0002232328,0.002078232,0.0005412251,0.0005370495,0.004131174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004683118,"about_ca_system_score_gemma":0.0002528071,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002289867,"about_ca_topic_score_gemma":0.002765196,"domain_scores_codex":[0.9997899,0.00001073478,0.000006744414,0.0001078249,0.00004426123,0.00004052241],"domain_scores_gemma":[0.9996676,0.0001005507,0.00003096713,0.00007069881,0.00007039525,0.00005973273],"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":[0.0006590224,0.0001009554,0.010114,0.000124535,0.00009800959,0.000567915,0.0004319469,0.0009041328,0.7026135,0.002647376,0.008657966,0.2730808],"study_design_scores_gemma":[0.000100845,0.0008479697,0.3215093,0.00009274556,0.0005814204,0.007210059,0.001434297,0.0805929,0.5342311,0.0155387,0.03771663,0.0001441526],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8900239,0.001431072,0.02989542,0.0005559193,0.000744899,0.00006605434,0.000527595,0.001116447,0.07563874],"genre_scores_gemma":[0.950493,0.0007703027,0.01118569,0.0005315712,0.0001438756,0.00001808283,0.0009887705,0.000167979,0.03570072],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01069792,"threshold_uncertainty_score":0.03578812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02899006031918873,"score_gpt":0.2926435005482309,"score_spread":0.2636534402290422,"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."}}