{"id":"W4247892711","doi":"10.1007/978-3-319-77525-8_161","title":"Big Data in Network Anomaly Detection","year":2019,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Big Data Technologies","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Anomaly detection; Anomaly (physics); Big data; Computer science; Data mining; Physics","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","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0008302758,0.0004729663,0.0006945585,0.0007027657,0.0001043146,0.00009785096,0.01031705,0.001119116,0.00001406802],"category_scores_gemma":[0.0003221762,0.0004676793,0.00006672569,0.0005395125,0.0002523691,0.001092622,0.01405264,0.001202229,0.0001387579],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000757169,"about_ca_system_score_gemma":0.0002270805,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001463847,"about_ca_topic_score_gemma":0.002105938,"domain_scores_codex":[0.9964424,0.00004062967,0.0008236471,0.001674061,0.0005304997,0.000488731],"domain_scores_gemma":[0.9891093,0.0002287654,0.0006786055,0.009870682,0.00007681621,0.00003583997],"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":[0.00001481855,0.00002218756,0.00008313504,0.00006521878,0.00003516435,0.00002242004,0.00001888113,0.00002313912,0.00001160473,0.01274473,0.009680497,0.9772782],"study_design_scores_gemma":[0.0002257102,0.0001865126,0.0001454112,0.0003651672,0.00003104834,0.00002210528,0.00001720448,0.005137462,0.0001104791,0.03937573,0.9538212,0.0005619316],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"other","genre_gemma":"review","genre_scores_codex":[0.0006370564,0.02501151,0.205678,0.001609318,0.02999357,0.002540152,0.001560377,0.005001605,0.7279684],"genre_scores_gemma":[0.2040127,0.4595172,0.08781232,0.0005798927,0.01427561,0.000147256,0.008557472,0.0006758709,0.2244217],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9767163,"threshold_uncertainty_score":0.9997775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06546547505728853,"score_gpt":0.2452520577327701,"score_spread":0.1797865826754815,"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."}}