{"id":"W6963586311","doi":"10.21227/dn9v-3278","title":"SCVIC-CIDS-2022: Bridging Networks and Hosts via Machine Learning-Based Intrusion Detection","year":2022,"lang":"en","type":"dataset","venue":"IEEE DataPort","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Intrusion detection system; Bridging (networking); Intrusion prevention system; Network security; Intrusion; Host-based intrusion detection system; Raw data","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":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002328645,0.001112687,0.001049699,0.00114086,0.001207938,0.0002967889,0.001118444,0.0006350357,0.01126316],"category_scores_gemma":[0.0004027848,0.001266515,0.0001939882,0.001306869,0.0002284425,0.0004942082,0.001087742,0.004369441,0.000730422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006576307,"about_ca_system_score_gemma":0.0002340682,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005676324,"about_ca_topic_score_gemma":0.004409292,"domain_scores_codex":[0.9938095,0.0006871367,0.001018834,0.001974601,0.001460719,0.001049224],"domain_scores_gemma":[0.9956581,0.0002664334,0.001292755,0.002253882,0.0001215143,0.0004073211],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003931237,0.0001511926,0.0004841705,0.0001854733,0.0001287358,0.0006375741,0.000006973732,0.0129378,0.0007787068,5.692498e-8,0.9783238,0.005972378],"study_design_scores_gemma":[0.001113107,0.0003106411,0.0004118659,0.0001265422,0.0004617372,0.0002857544,0.000007696095,0.06550995,0.0002895865,0.000002222749,0.9302813,0.001199584],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001505314,0.0008508349,0.00408965,0.0000331595,0.002936586,0.000915125,0.9891153,0.0005462569,0.000007770845],"genre_scores_gemma":[0.005484215,0.0003531738,0.00003028223,0.0004460383,0.001159188,0.0001920042,0.9918908,0.0003670168,0.00007726429],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05257215,"threshold_uncertainty_score":0.9989784,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009584085165176661,"score_gpt":0.2422875192880571,"score_spread":0.2327034341228804,"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."}}