{"id":"W3145571801","doi":"10.21810/jicw.v3i3.2752","title":"Detecting and Combating Deep Fakes","year":2021,"lang":"en","type":"article","venue":"The Journal of Intelligence Conflict and Warfare","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Misinformation; Presentation (obstetrics); Computer security; Political science; Internet privacy; Computer science; Medicine","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":[0.0006776454,0.00007735052,0.0001238247,0.00004561964,0.0002435149,0.0001842234,0.0002700199,0.00003489502,0.000007654124],"category_scores_gemma":[0.0002775775,0.00005114184,0.00003284132,0.0001610843,0.00005140536,0.0002809055,0.0001190785,0.0002408726,0.000001296817],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009378055,"about_ca_system_score_gemma":0.00002840491,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001774643,"about_ca_topic_score_gemma":0.00001454962,"domain_scores_codex":[0.9992987,0.0000984334,0.0002436189,0.00008814791,0.0001532378,0.0001178424],"domain_scores_gemma":[0.9990056,0.0003768927,0.0001827809,0.000141398,0.0002298881,0.0000634209],"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":[0.00002436381,0.00001742866,0.002393309,0.00003523994,0.00005298534,0.00005244532,0.02276155,0.0003350443,0.01197137,0.003838765,0.0000388824,0.9584786],"study_design_scores_gemma":[0.0006595177,0.001341451,0.01857168,0.0008619786,0.000171047,0.01523495,0.02441769,0.1731814,0.7233844,0.02595926,0.01533872,0.0008779505],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.488656,0.01066994,0.4987519,0.001221212,0.0003832009,0.00003485518,2.341359e-7,0.00001844414,0.0002641323],"genre_scores_gemma":[0.9956102,0.001122736,0.002898499,0.000237483,0.00009439362,2.593403e-7,5.827046e-8,0.000003730955,0.00003259019],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9576007,"threshold_uncertainty_score":0.2085504,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02923402695146751,"score_gpt":0.2632571747400946,"score_spread":0.2340231477886271,"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."}}