{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001876454,0.00005337941,0.00005655406,0.00006489102,0.0006170289,0.000109784,0.0001323519,0.00002079805,0.00004355],"category_scores_gemma":[0.000006328792,0.00006013174,0.00001905984,0.0002960068,0.0000110734,0.0003554475,0.0002940402,0.0001822792,0.000005206112],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004979265,"about_ca_system_score_gemma":0.00001537549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008586622,"about_ca_topic_score_gemma":0.00002907004,"domain_scores_codex":[0.9993651,0.00007321187,0.00008688472,0.0001942765,0.000151212,0.0001293156],"domain_scores_gemma":[0.9997276,0.00002223272,0.00003825255,0.0001591387,0.00002072239,0.00003203786],"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":[0.00002839464,0.00007568787,0.00059447,0.0000164484,0.00002352419,0.00003375002,0.002995573,0.01296774,0.07303917,0.01308031,0.001058696,0.8960862],"study_design_scores_gemma":[0.0002359227,0.0002434487,0.0005481768,0.000006833409,0.00000490361,0.0001668793,0.0000662851,0.9148225,0.01741439,0.007311291,0.05899501,0.0001843167],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6795641,0.0001603853,0.3189155,0.000200213,0.000682816,0.00005856753,4.032479e-7,0.00008849266,0.000329501],"genre_scores_gemma":[0.9972159,0.000008059164,0.001845677,0.0007801076,0.00008468818,0.000005534629,3.178308e-7,0.000004420669,0.00005532105],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9018548,"threshold_uncertainty_score":0.474575,"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."}}