{"id":"W4402402145","doi":"10.2139/ssrn.4943841","title":"Deepfakes in Court: How Judges Can Proactively Manage Alleged AI-Generated Material in National Security Cases","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University; University of Waterloo","funders":"","keywords":"National security; Law; Computer security; Political science; Psychology; Business; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.007748527,0.0003469646,0.0004792712,0.0005521576,0.000487939,0.001311776,0.0005957199,0.0008021264,0.00005016863],"category_scores_gemma":[0.001136415,0.0003515262,0.0001766954,0.000442173,0.0002669089,0.0003276259,0.0002768545,0.009071743,0.000005986701],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.006997991,"about_ca_system_score_gemma":0.0208474,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.0201117,"about_ca_topic_score_gemma":0.6519114,"domain_scores_codex":[0.9945661,0.001013714,0.0004472165,0.0004857033,0.00112885,0.002358445],"domain_scores_gemma":[0.9986998,0.0001604193,0.0002922502,0.0001177886,0.0005632801,0.0001664606],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002404909,0.0002841895,0.001779558,0.0001528248,0.0005736074,0.00046828,0.04378523,0.0002774814,0.0002529941,0.9491976,0.001509379,0.001478384],"study_design_scores_gemma":[0.0003985614,0.00008996317,0.0006086027,0.0001669201,0.00003906856,0.00003996658,0.01593641,0.0001046355,0.0000900737,0.9811345,0.0009755707,0.0004156854],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9186897,0.001702881,0.000009141847,0.07057342,0.001278093,0.0006024108,0.0001590422,0.00006688148,0.006918391],"genre_scores_gemma":[0.989952,0.007025525,0.00002189151,0.0003381792,0.001666883,0.00003558898,0.00006131452,0.00004515987,0.0008534875],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6317997,"threshold_uncertainty_score":0.9998937,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0311603778740511,"score_gpt":0.3425642646053496,"score_spread":0.3114038867312985,"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."}}