{"id":"W4404999639","doi":"10.9734/ajrcos/2024/v17i12528","title":"Artificial Intelligence and Information Governance: Strengthening Global Security, through Compliance Frameworks, and Data Security","year":2024,"lang":"en","type":"article","venue":"Asian Journal of Research in Computer Science","topic":"Information and Cyber Security","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centennial College","funders":"","keywords":"Corporate governance; Information security; Vulnerability (computing); Computer science; Knowledge management; Process management; Business; Computer security; Finance","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":["scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.006358874,0.0001450453,0.0002051968,0.0003241019,0.0003291414,0.002988624,0.003104314,0.0001025927,0.000004145174],"category_scores_gemma":[0.000260182,0.0001276945,0.00002796619,0.002951464,0.0009050672,0.01961634,0.002595715,0.001386575,0.00001403801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001730494,"about_ca_system_score_gemma":0.0006871333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003081825,"about_ca_topic_score_gemma":0.00002016785,"domain_scores_codex":[0.9965659,0.0001648117,0.0007219298,0.0004059312,0.00160167,0.0005397259],"domain_scores_gemma":[0.9981971,0.0002360533,0.0001848935,0.0006402888,0.0005051166,0.0002365727],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008495773,0.00002343227,0.0002213142,0.0000906893,0.000005299431,0.00005733273,0.008809655,0.00007933239,9.891598e-7,0.4390617,0.0002372109,0.5514045],"study_design_scores_gemma":[0.00006252633,0.0001416856,0.001457681,0.0006597969,0.000001412205,0.0004729292,0.0003385587,0.7076674,0.00006166108,0.2867182,0.002286316,0.0001318791],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0169405,0.001229675,0.9663861,0.01305969,0.001177275,0.0001730236,0.00002190618,0.00004407661,0.0009677041],"genre_scores_gemma":[0.9300912,0.0004291277,0.06910703,0.0002075918,0.0001598378,0.000001125427,0.000001312584,0.000002390904,3.7054e-7],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9131507,"threshold_uncertainty_score":0.9980464,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0971082563661716,"score_gpt":0.4080761515011661,"score_spread":0.3109678951349945,"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."}}