{"id":"W4414052751","doi":"10.2139/ssrn.5425098","title":"Leveraging Artificial Intelligence for Cyber Threat Intelligence: Perspectives from the U.S., Canada, and Japan","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Intelligence, Security, War Strategy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Leverage (statistics); Malware; Vulnerability (computing); Cyber threats; Anomaly detection; Key (lock); Big data; Human intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.004130094,0.0005085503,0.0005419917,0.0001510704,0.002219851,0.000717938,0.001759046,0.0004402348,0.0001280067],"category_scores_gemma":[0.0008974897,0.000425536,0.0002959511,0.0003370762,0.0007082071,0.0001766241,0.0004033391,0.005492222,0.000005466773],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.004588716,"about_ca_system_score_gemma":0.03523769,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8329053,"about_ca_topic_score_gemma":0.9839638,"domain_scores_codex":[0.9939325,0.0005280215,0.0007931284,0.000860311,0.0008728404,0.00301317],"domain_scores_gemma":[0.996988,0.001242013,0.0004530969,0.0004561713,0.0006638891,0.0001968185],"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":[0.00007039026,0.00004689015,0.0006486141,0.00001577435,0.0004022923,0.00000344273,0.04890106,0.0003965349,0.000004701529,0.8609292,0.0002429117,0.0883382],"study_design_scores_gemma":[0.00002570632,0.00005198043,0.0001180399,0.0001258346,0.0001245314,0.00001138787,0.2389039,0.0003456777,0.0001571785,0.7575193,0.00224387,0.0003726281],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.446143,0.1133363,0.347398,0.05484888,0.01216909,0.00537745,0.0006421374,0.000287978,0.01979721],"genre_scores_gemma":[0.9730181,0.02173369,0.0002851332,0.0002421349,0.002561176,0.00005797474,0.00001844093,0.00003330979,0.002050059],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5268751,"threshold_uncertainty_score":0.9998196,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03289377105485061,"score_gpt":0.3182273790216537,"score_spread":0.2853336079668031,"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."}}