{"id":"W2071526585","doi":"10.1167/6.6.876","title":"Effects of synthetic face adaptation: An fMRI study","year":2010,"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":"York University","funders":"","keywords":"Fusiform face area; Psychology; Adaptation (eye); Face (sociological concept); Perception; Identity (music); Face perception; Cognitive psychology; Contrast (vision); Facial recognition system; Task (project management); Psychophysics; Neuroscience; Communication; Pattern recognition (psychology); Artificial intelligence; Computer science","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":[0.0002568418,0.0002799122,0.0002095476,0.0001435036,0.0001102305,0.0001392936,0.0001696058,0.0002507695,0.000932879],"category_scores_gemma":[0.0009972996,0.000109413,0.000216649,0.00009535479,0.0002649298,0.0001832435,0.0002503273,0.0004480401,0.00009439472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001239502,"about_ca_system_score_gemma":0.00008547535,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003903342,"about_ca_topic_score_gemma":0.0003557373,"domain_scores_codex":[0.9998881,0.00002863307,0.000008618425,0.00002721607,0.00002693113,0.00002054435],"domain_scores_gemma":[0.9997128,0.000128782,0.00004005256,0.00005461198,0.00003382911,0.00002997979],"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":[0.0006499619,0.000155626,0.000283863,0.00004157828,0.00001339421,0.00008370991,0.00003216505,0.0003225211,0.9948331,0.0000658997,0.00003307006,0.003485029],"study_design_scores_gemma":[0.0001308519,0.009335964,0.06454609,0.00001768909,0.0001370111,0.002586789,0.0001174187,0.01218644,0.9078623,0.000720177,0.002308057,0.0000512393],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949579,0.0002476297,0.003722906,0.00004347117,0.00003742713,0.00004416387,0.00006958614,0.00002441155,0.0008525994],"genre_scores_gemma":[0.9950674,0.0002559824,0.003793056,0.00008709726,0.00003957583,0.00005073347,0.0001288275,0.00002604891,0.0005512231],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.000932879,"threshold_uncertainty_score":0.00312078,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01104325540053458,"score_gpt":0.2838451040555203,"score_spread":0.2728018486549857,"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."}}