{"id":"W4205437586","doi":"10.3390/ai3010002","title":"Cyberattack and Fraud Detection Using Ensemble Stacking","year":2022,"lang":"en","type":"article","venue":"AI","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Credit card fraud; Internet of Things; Classifier (UML); Ensemble learning; Process (computing); Machine learning; Artificial intelligence; Data mining; Computer security; Credit card; World Wide Web","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002378301,0.001407444,0.001788383,0.004086799,0.001096174,0.001642143,0.001411834,0.001212222,0.0007569643],"category_scores_gemma":[0.004010103,0.0003375019,0.001420884,0.002204615,0.0004282691,0.002245151,0.00131232,0.001667723,0.0005176382],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008060772,"about_ca_system_score_gemma":0.001045177,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009042129,"about_ca_topic_score_gemma":0.009203811,"domain_scores_codex":[0.9985113,0.0002768335,0.0001135913,0.0002850011,0.0004994998,0.0003139323],"domain_scores_gemma":[0.9972355,0.0005826998,0.0002903672,0.0005792517,0.00111479,0.0001974385],"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":[0.0006774861,0.0008902643,0.08137253,0.00008427315,0.0008553452,0.0006093024,0.0002523686,0.2104886,0.007438094,0.002537083,0.01179858,0.6829962],"study_design_scores_gemma":[0.000005373762,0.00008692421,0.005243823,0.000009360235,0.00006033428,0.0001140579,0.0000557612,0.9896262,0.002846613,0.001131309,0.0008021703,0.00001813059],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6940606,0.002638065,0.2923015,0.00102233,0.000605822,0.0002382773,0.001070218,0.002505476,0.005557697],"genre_scores_gemma":[0.9617639,0.0003782414,0.03510205,0.00009610403,0.0001049833,0.00003531625,0.0009616581,0.00002191753,0.001535917],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009042129,"threshold_uncertainty_score":0.01797903,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01770767198629035,"score_gpt":0.2480302187348651,"score_spread":0.2303225467485748,"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."}}