{"id":"W4408133719","doi":"10.18280/mmep.120219","title":"Behavior of Visual Content in Deepfake Generated Based on Conditional Generative Adversarial Networks","year":2025,"lang":"en","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Generative grammar; Adversarial system; Content (measure theory); Computer science; Generative adversarial network; Artificial intelligence; Machine learning; Econometrics; Mathematics; Image (mathematics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002730956,0.00017169,0.0002854268,0.0001508371,0.00005100687,0.00006091331,0.000145344,0.00009164187,0.000006275287],"category_scores_gemma":[0.00003044338,0.0001521235,0.00005476147,0.0002362797,0.00003597721,0.00008339588,0.00004865923,0.0001604792,0.000001028652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003138643,"about_ca_system_score_gemma":0.00002840199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001208058,"about_ca_topic_score_gemma":0.000001341611,"domain_scores_codex":[0.9989444,0.00004261337,0.0003599587,0.0002817002,0.00014743,0.0002239072],"domain_scores_gemma":[0.9994684,0.0002074187,0.00004959064,0.0001493965,0.00006815456,0.00005704653],"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":[0.000009011985,0.0001466048,0.00002468253,0.00004589704,0.00001562367,0.000002677167,0.00006616118,0.9673823,0.0008867065,0.03090905,0.00001359756,0.0004977022],"study_design_scores_gemma":[0.0005188627,0.00007865162,0.00006379655,0.0002091527,0.00001514016,8.133632e-7,0.000004791203,0.9951944,0.001895301,0.001861828,0.00001935423,0.0001379527],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01366683,0.00008765338,0.9855723,0.0001073709,0.0001375814,0.0002421477,0.000002497661,0.00004582326,0.0001377549],"genre_scores_gemma":[0.8895233,0.000008039245,0.1102473,0.00006566793,0.00003496849,0.0000664429,0.00000749441,0.000008408937,0.00003846447],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8758564,"threshold_uncertainty_score":0.6203418,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02524425503877913,"score_gpt":0.2270222837456355,"score_spread":0.2017780287068563,"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."}}