{"id":"W4310415410","doi":"10.48550/arxiv.2211.14667","title":"Deep Fake Detection, Deterrence and Response: Challenges and Opportunities","year":2022,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cybercrime; Hacker; Computer security; Deterrence theory; Internet privacy; Hoax; Software deployment; Identification (biology); Computer science; Business; Political science; Law; World Wide Web; The Internet","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005383444,0.001489842,0.001194465,0.002357262,0.00116929,0.003980695,0.002594114,0.0046112,0.002571438],"category_scores_gemma":[0.01995658,0.0007141015,0.0006608404,0.000943217,0.003132173,0.007825535,0.002862771,0.005271973,0.002181227],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001301828,"about_ca_system_score_gemma":0.001495113,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002024831,"about_ca_topic_score_gemma":0.002048139,"domain_scores_codex":[0.9951309,0.001427069,0.0003093434,0.0005520661,0.002087955,0.0004926181],"domain_scores_gemma":[0.9861329,0.007639146,0.001359227,0.00177062,0.002622106,0.0004761666],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002287582,0.0002725812,0.006561438,0.001141834,0.0001147024,0.0004728657,0.0007495423,0.0175159,0.009313645,0.03683117,0.02992785,0.8968697],"study_design_scores_gemma":[0.00006922218,0.0007227012,0.007352286,0.001899372,0.0001851424,0.004165638,0.00198003,0.6136532,0.0514328,0.1694394,0.1487366,0.0003636656],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06475358,0.08832572,0.7626862,0.04727535,0.001849402,0.0004223261,0.0005255549,0.005605008,0.02855688],"genre_scores_gemma":[0.7120366,0.03297532,0.229471,0.007004246,0.00137732,0.0002249273,0.0007569428,0.0003251441,0.01582859],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005383444,"threshold_uncertainty_score":0.02847075,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1320925092406114,"score_gpt":0.2086241897741513,"score_spread":0.07653168053353987,"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."}}