{"id":"W4402978005","doi":"10.1145/3640310.3674087","title":"Enhancing Automata Learning with Statistical Machine Learning: A Network Security Case Study","year":2024,"lang":"en","type":"article","venue":"","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Learning automata; Artificial intelligence; Automaton; Machine learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003059272,0.0005337412,0.0003538363,0.0006771206,0.0006129605,0.000968923,0.001127309,0.001149737,0.001244023],"category_scores_gemma":[0.0108771,0.0002229869,0.0005959597,0.0007076005,0.00129971,0.001419287,0.0009504347,0.001431429,0.0001850931],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00158453,"about_ca_system_score_gemma":0.001096294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009510553,"about_ca_topic_score_gemma":0.01185666,"domain_scores_codex":[0.9979112,0.001169832,0.0001021557,0.0002291485,0.0004463675,0.0001412873],"domain_scores_gemma":[0.9871705,0.01042627,0.0003422566,0.0009416587,0.0009497151,0.0001696696],"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":[0.0003530798,0.0005654191,0.01570524,0.0002171555,0.00007372269,0.001035142,0.0006732556,0.8755189,0.00452424,0.01892633,0.00151819,0.08088943],"study_design_scores_gemma":[0.00002892906,0.0001170601,0.0008674019,0.00001074541,0.00001317486,0.00009769166,0.00009690674,0.9829699,0.005859742,0.008581795,0.001344945,0.00001175871],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6934811,0.000489016,0.293566,0.002119787,0.00006704834,0.0003888553,0.0004541919,0.001534924,0.007899039],"genre_scores_gemma":[0.9162557,0.0001126299,0.08209346,0.00008314523,0.00001514833,0.00009167073,0.0001622311,0.00003897463,0.001147077],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009510553,"threshold_uncertainty_score":0.01891041,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009716219523804194,"score_gpt":0.2531664250603147,"score_spread":0.2434502055365105,"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."}}