{"id":"W4409284266","doi":"10.1007/s00138-025-01687-8","title":"Emotion-aware face de-identification with generative adversarial networks","year":2025,"lang":"en","type":"article","venue":"Machine Vision and Applications","topic":"Face recognition and analysis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Adversarial system; Generative grammar; Identification (biology); Face (sociological concept); Computer science; Artificial intelligence; Noma; Speech recognition; Telecommunications; Linguistics; Philosophy","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":[0.0008598919,0.0009643477,0.0008534124,0.0004449498,0.0003366179,0.0006352391,0.001211784,0.001083825,0.002544791],"category_scores_gemma":[0.00189075,0.000492636,0.001000346,0.0003664416,0.0004788321,0.0008029898,0.001546005,0.002162612,0.002037547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004243671,"about_ca_system_score_gemma":0.0004545609,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002008761,"about_ca_topic_score_gemma":0.003467211,"domain_scores_codex":[0.9994847,0.0001365292,0.00001648777,0.0001440254,0.0001330806,0.00008521498],"domain_scores_gemma":[0.9993836,0.0002964516,0.00004775748,0.0001348723,0.000111836,0.00002546597],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003857306,0.0001846058,0.001236892,0.0001010276,0.0001778986,0.0001677726,0.00008698201,0.4731801,0.03738694,0.00928872,0.007183291,0.47062],"study_design_scores_gemma":[0.000002926921,0.0000171982,0.0002361529,0.000005455764,0.00001046254,0.00005542089,0.000006370337,0.992632,0.004281329,0.002271754,0.0004745528,0.000006419186],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01446843,0.0003531684,0.9816305,0.0002483602,0.0001166959,0.00004572394,0.0001106041,0.001065118,0.001961432],"genre_scores_gemma":[0.6673632,0.0006472807,0.3123752,0.0007761766,0.0001849802,0.000180312,0.0009969457,0.0004020813,0.01707386],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002544791,"threshold_uncertainty_score":0.008513153,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004380545785906225,"score_gpt":0.2584465745580697,"score_spread":0.2540660287721634,"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."}}