{"id":"W4220837197","doi":"10.1051/itmconf/20224301015","title":"Withdraw article: A Survey on Network Intrusion Detection using Convolutional Neural Network","year":2022,"lang":"en","type":"article","venue":"ITM Web of Conferences","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Convolutional neural network; Computer science; Intrusion; Artificial neural network; Volume (thermodynamics); Intrusion detection system; Artificial intelligence; Geology","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":[0.001198284,0.0001735412,0.000256685,0.0001130189,0.0008337699,0.0001073175,0.0005837029,0.0000698567,0.0003045445],"category_scores_gemma":[0.00005434928,0.0001717932,0.0000813542,0.001164311,0.000116585,0.0003082203,0.0004300377,0.0003979629,0.000007576359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007476129,"about_ca_system_score_gemma":0.0005034012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006783954,"about_ca_topic_score_gemma":0.0007553938,"domain_scores_codex":[0.997409,0.0007336914,0.0004144053,0.000408549,0.0006338877,0.0004004683],"domain_scores_gemma":[0.9987536,0.0003380603,0.0003148784,0.0003349695,0.0001722519,0.00008620507],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007699673,0.0002691345,0.04541814,0.0000153588,0.00008232028,0.00001330646,0.0002791587,0.7866281,0.002773838,0.09315976,0.005045452,0.06554548],"study_design_scores_gemma":[0.0003833458,0.0007091113,0.06076359,0.00002943503,0.000009278322,0.00002567713,0.00002309407,0.925773,0.000771846,0.005704594,0.005578774,0.0002282626],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.963053,0.0002367701,0.03216903,0.000179956,0.002968573,0.0002344243,0.000009628691,0.000132176,0.001016396],"genre_scores_gemma":[0.9985602,0.00001843632,0.0006801061,0.0002718866,0.0004065693,0.00001710202,0.000008671136,0.000008133309,0.00002882689],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1391449,"threshold_uncertainty_score":0.7005522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03346890789542771,"score_gpt":0.2506534166073155,"score_spread":0.2171845087118878,"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."}}