{"id":"W2517343942","doi":"10.1145/2975961.2975962","title":"Mining timed regular expressions from system traces","year":2016,"lang":"en","type":"article","venue":"","topic":"Software Testing and Debugging Techniques","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Debugging; Computer science; Rotation formalisms in three dimensions; Event (particle physics); Anomaly (physics); Anomaly detection; Programming language; Temporal logic; Real-time computing; Data mining","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":[0.0001748553,0.00009201439,0.0001140668,0.0000551366,0.00009501261,0.00007292509,0.0006440724,0.00005199335,0.00002239415],"category_scores_gemma":[0.0001530859,0.00005216113,0.00003637586,0.0001131142,0.00002476852,0.0002469121,0.0001753311,0.00002939734,0.00007141609],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000262831,"about_ca_system_score_gemma":0.00002364363,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007671014,"about_ca_topic_score_gemma":0.00000119146,"domain_scores_codex":[0.999148,0.00005230909,0.0001485532,0.0003037698,0.0001721464,0.0001752466],"domain_scores_gemma":[0.9984997,0.0006847798,0.00005667289,0.0006438111,0.00003820042,0.00007682699],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000008096271,0.00008088888,0.009116388,0.0000247618,0.00004113646,0.0001002474,0.001431421,0.000002285113,0.04841759,0.02455773,0.3549804,0.5612391],"study_design_scores_gemma":[0.002961231,0.0005369336,0.02049936,0.01002167,0.00006946483,0.0002506653,0.0003398964,0.1580764,0.6144711,0.1582416,0.03129166,0.003239938],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02448103,0.00007754529,0.9481971,0.0007140223,0.0001731372,0.00005698963,0.000001732514,0.02293772,0.003360729],"genre_scores_gemma":[0.5175595,8.201615e-7,0.4816479,0.0000510369,0.0000390073,0.00001218584,2.813817e-7,0.000005056486,0.0006841708],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5660536,"threshold_uncertainty_score":0.2127069,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01949574828471648,"score_gpt":0.2332083157025829,"score_spread":0.2137125674178664,"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."}}