{"id":"W3013157084","doi":"10.1007/978-3-030-44041-1_118","title":"Intrusion Detection Using ASTDs","year":2020,"lang":"en","type":"book-chapter","venue":"Advances in intelligent systems and computing","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Computer science; False positive paradox; Executable; Intrusion detection system; Scripting language; Programming language; Modular design; Data mining; Artificial intelligence","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"],"consensus_categories":[],"category_scores_codex":[0.0003404182,0.0003571293,0.0004911424,0.000271134,0.0002458826,0.000225734,0.0003974088,0.0002712296,0.000007808239],"category_scores_gemma":[0.00002149167,0.0003632446,0.0000915817,0.0001645372,0.0000545519,0.0005025464,0.0005237521,0.000619907,0.00002476356],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001695544,"about_ca_system_score_gemma":0.00002870748,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006078317,"about_ca_topic_score_gemma":0.00004120256,"domain_scores_codex":[0.9978396,0.00006268553,0.0007388031,0.0007556661,0.0003315627,0.0002716439],"domain_scores_gemma":[0.9988919,0.0001276101,0.0004726675,0.0003178846,0.00008098738,0.0001089334],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001706015,0.00001082016,0.00001927617,0.0002881605,0.00002148044,0.00003936845,0.0004553779,0.01969106,0.0001154289,0.2492599,0.00001025146,0.7300718],"study_design_scores_gemma":[0.0001029855,0.0001676535,0.000003628913,0.001379142,0.00001016984,0.0001235292,0.00004129051,0.8289221,0.0002282397,0.01320842,0.1553816,0.0004312477],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0008082061,0.02198567,0.9436651,0.00002818358,0.00395284,0.0004304491,0.000001498999,0.0001947654,0.02893328],"genre_scores_gemma":[0.9820701,0.007648751,0.005339149,0.0001821804,0.001879567,0.000007503781,0.000005447214,0.00007620937,0.002791096],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9812619,"threshold_uncertainty_score":0.9998819,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0229175766304166,"score_gpt":0.2558266050981347,"score_spread":0.2329090284677181,"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."}}