{"id":"W2113224047","doi":"10.1145/1866480.1866487","title":"NeuDetect","year":2010,"lang":"en","type":"article","venue":"","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Intrusion detection system; Constant false alarm rate; Network packet; Artificial neural network; Wireless network; Wireless; Computer network; False alarm; Anomaly-based intrusion detection system; Data mining; Real-time computing; Artificial intelligence; Telecommunications","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":[0.00009284724,0.00003188302,0.00002984297,0.00002801586,0.00006299234,0.00006710592,0.0002965884,0.00003222949,0.0002573925],"category_scores_gemma":[0.00001135177,0.00002590319,0.0000206204,0.0001494468,0.00001078857,0.0002363543,0.0000801238,0.0001378525,0.0002639575],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001595145,"about_ca_system_score_gemma":0.000007337044,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001250221,"about_ca_topic_score_gemma":0.00006198901,"domain_scores_codex":[0.999675,0.000007565118,0.00004903636,0.000110633,0.00007175674,0.00008602304],"domain_scores_gemma":[0.9996637,0.00001704528,0.00001108701,0.0002547344,0.00001650421,0.00003692678],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001195134,0.0000212533,0.00005444011,9.1974e-7,0.000001787343,0.000002653376,0.00007063524,0.00000449075,0.04353755,0.5644726,0.004728522,0.387104],"study_design_scores_gemma":[0.0002031575,0.000114739,0.002613266,0.000001895275,0.000001193908,0.00007841612,0.000003112469,0.1904609,0.1468243,0.04654524,0.6129249,0.0002288055],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2514214,0.000008132318,0.648038,0.001539426,0.002922059,0.00006269183,7.017111e-8,0.0006096853,0.09539852],"genre_scores_gemma":[0.9758991,0.00000201459,0.02285435,0.0004963302,0.0001441003,0.000002048751,5.494103e-8,0.000001485954,0.0006004906],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7244777,"threshold_uncertainty_score":0.3392727,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006469099799361805,"score_gpt":0.2114240029291827,"score_spread":0.2049549031298209,"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."}}