{"id":"W7019435703","doi":"","title":"Generalization of a Constraint Based Intrusion Detection System","year":2020,"lang":"en","type":"dissertation","venue":"QSpace (Queen's University Library)","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Queen's University","keywords":"Digital subscriber line; Constraint (computer-aided design); Network packet; Domain (mathematical analysis); Generalization; Intrusion detection system; Variety (cybernetics); Sequence (biology)","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00007369627,0.0002905591,0.0004401452,0.0004030509,0.0001920341,0.00007656868,0.0007656158,0.000415067,0.00003252735],"category_scores_gemma":[0.00002402198,0.0003049203,0.0002136863,0.001012681,0.00005009122,0.001175884,0.0001354739,0.0002724039,0.00002766258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001799091,"about_ca_system_score_gemma":0.0005448904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000985716,"about_ca_topic_score_gemma":0.00002682871,"domain_scores_codex":[0.9982548,0.0002281255,0.0003067705,0.0005963891,0.0003981051,0.0002157484],"domain_scores_gemma":[0.9985518,0.00006501221,0.0005152424,0.000564116,0.0001553264,0.0001484278],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.009321559,0.002939365,0.09019927,0.1235285,0.003068387,0.002604729,0.05501789,0.02466455,0.01437154,0.2713481,0.2291259,0.1738102],"study_design_scores_gemma":[0.005980668,0.0022047,0.03196938,0.006898156,0.0006955519,0.000007496506,0.01472605,0.1034764,0.6899441,0.0004244416,0.1389045,0.004768593],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1828649,0.00006623261,0.7845504,0.009883407,0.004399132,0.002132491,0.00008780514,0.003309797,0.01270579],"genre_scores_gemma":[0.983936,0.00004615381,0.01108371,0.00005235877,0.00008755621,0.000002400047,0.0003793214,0.00003073733,0.004381813],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.801071,"threshold_uncertainty_score":0.9999403,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004890740538879874,"score_gpt":0.1748457845770339,"score_spread":0.169955044038154,"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."}}