{"id":"W4408426509","doi":"10.3758/s13428-025-02636-z","title":"Unraveling other-race face perception with GAN-based image reconstruction","year":2025,"lang":"en","type":"article","venue":"Behavior Research Methods","topic":"Face recognition and analysis","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"","keywords":"Race (biology); Similarity (geometry); Artificial intelligence; Face (sociological concept); Pairwise comparison; Computer science; Perception; Face perception; Basis (linear algebra); Pattern recognition (psychology); Cognitive psychology; Computer vision; Psychology; Image (mathematics); Mathematics; Geology; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00427743,0.0001449021,0.000211007,0.0008033929,0.0004013705,0.0003982338,0.0005690302,0.00009818647,0.0002400423],"category_scores_gemma":[0.0002742286,0.0001233329,0.0001058793,0.002152306,0.0002113758,0.0003887395,0.00006766449,0.0005046751,0.00008168052],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001807598,"about_ca_system_score_gemma":0.0002912329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000179062,"about_ca_topic_score_gemma":0.0000324078,"domain_scores_codex":[0.9963533,0.00185525,0.0002419938,0.0005732415,0.0005426604,0.0004335305],"domain_scores_gemma":[0.9981825,0.0004316535,0.00005806904,0.0006088914,0.0005906383,0.0001282599],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001562863,0.00009787212,0.001546609,0.00002280084,0.00001355049,0.000008642193,0.0001687578,0.00005854965,0.2199491,0.000285301,0.00007780211,0.7777554],"study_design_scores_gemma":[0.001932517,0.0003929834,0.02711169,0.0005381344,0.0001275968,0.00005587877,0.004704452,0.3151468,0.6420343,0.001677247,0.005457935,0.0008205075],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05994524,0.00003331762,0.935872,0.001361746,0.0001084497,0.0003241587,0.000003727441,0.0001605797,0.002190803],"genre_scores_gemma":[0.08368713,0.00002020893,0.9138585,0.0001149908,0.00002288414,0.0001586289,0.000004312587,0.00001366146,0.002119687],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7769349,"threshold_uncertainty_score":0.5029371,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1481027888250592,"score_gpt":0.52501069815385,"score_spread":0.3769079093287909,"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."}}