{"id":"W2034196084","doi":"10.3758/s13428-010-0029-9","title":"A computer-generated face database with ratings on realism, masculinity, race, and stereotypy","year":2010,"lang":"en","type":"article","venue":"Behavior Research Methods","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Masculinity; Psychology; Perception; Race (biology); Ethnic group; Set (abstract data type); Face perception; Face (sociological concept); Social psychology; Cognitive psychology; Computer science; Gender studies; Sociology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003860933,0.0001791903,0.0002093782,0.0002874668,0.000452213,0.000283068,0.0002661521,0.0001206092,0.0005041566],"category_scores_gemma":[0.0007719066,0.0001394672,0.00003412144,0.0006009018,0.0004595661,0.0002460335,0.0002041423,0.001316938,0.000128462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000233447,"about_ca_system_score_gemma":0.00008367707,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001499061,"about_ca_topic_score_gemma":0.0001174353,"domain_scores_codex":[0.9950956,0.002879155,0.0002069858,0.0006767745,0.000686405,0.0004550636],"domain_scores_gemma":[0.9979304,0.0009946825,0.00005688268,0.0005045336,0.0001953835,0.0003180924],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001173085,0.0001920156,0.000460608,0.00001616436,0.000001496756,0.00004781587,0.0003878112,0.000001757459,0.8488895,0.0002169321,0.000586466,0.1490821],"study_design_scores_gemma":[0.001953426,0.001140119,0.01838632,0.00008799836,0.00002323597,0.000259008,0.0003512191,0.004621176,0.9561323,0.00007799434,0.01648073,0.0004864921],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9882775,0.000004268717,0.009192457,0.0005843152,0.0002009865,0.0007870697,0.0001011769,0.0001116956,0.0007405297],"genre_scores_gemma":[0.643367,0.0002268473,0.352524,0.0006618879,0.0002884001,0.0004111425,0.0001125402,0.00008649215,0.002321667],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3449105,"threshold_uncertainty_score":0.5721512,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.358130814821676,"score_gpt":0.5455536191535534,"score_spread":0.1874228043318774,"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."}}