{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001113985,0.0007992118,0.0005654859,0.001791672,0.0006589545,0.002022604,0.002245689,0.001241804,0.02703512],"category_scores_gemma":[0.004076581,0.0004276844,0.0006052104,0.00103416,0.0005109992,0.002923094,0.002440136,0.001259893,0.01739678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008556014,"about_ca_system_score_gemma":0.001579782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004100375,"about_ca_topic_score_gemma":0.007082791,"domain_scores_codex":[0.9985301,0.0001323097,0.00007823034,0.000237422,0.0009221238,0.00009978122],"domain_scores_gemma":[0.9984288,0.0002896136,0.0000874646,0.0003859566,0.000708359,0.00009990553],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004705324,0.0001573338,0.004289123,0.0003171785,0.00006326053,0.000303981,0.0001820923,0.005452964,0.008729837,0.03634828,0.1585351,0.7851502],"study_design_scores_gemma":[0.0001075886,0.0002080535,0.002814286,0.0001274325,0.0000692083,0.001461845,0.00009030528,0.07647616,0.0356757,0.02052309,0.8623174,0.0001290916],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.0233559,0.002012437,0.6833985,0.002808802,0.001559008,0.0006329622,0.00639252,0.0884599,0.1913799],"genre_scores_gemma":[0.1375765,0.002257394,0.5271117,0.002990014,0.0003426739,0.0004697243,0.02035545,0.005318191,0.3035784],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.02703512,"threshold_uncertainty_score":0,"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."}}