{"id":"W2047587707","doi":"10.1109/mascots.2012.22","title":"MMPP Characterization of Web Application Traffic","year":2012,"lang":"en","type":"article","venue":"","topic":"Network Traffic and Congestion Control","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Burstiness; Computer science; Provisioning; TRACE (psycholinguistics); Markovian arrival process; Context (archaeology); Markov process; Poisson distribution; Real-time computing; Queueing theory; Computer network; Mathematics; Statistics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001392413,0.00005049191,0.00007127478,0.0000355768,0.00002554645,0.00001429437,0.0002115026,0.00003097189,0.00002059826],"category_scores_gemma":[0.000003018851,0.00004429925,0.0000251265,0.0001910139,0.00001212433,0.0003596466,0.00002255132,0.00002948261,0.00007619448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007332811,"about_ca_system_score_gemma":0.00001810742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":4.901648e-7,"about_ca_topic_score_gemma":6.438012e-7,"domain_scores_codex":[0.9995247,0.00002176078,0.0001327854,0.00009721463,0.0001024774,0.0001211254],"domain_scores_gemma":[0.9996076,0.00002039768,0.00006612753,0.0002123286,0.00004093382,0.00005262248],"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":[0.000001971017,0.00006464161,0.0005356224,0.000003403002,0.000004718056,3.584689e-8,0.00008852804,0.00008766977,0.0223063,0.158791,0.00009414721,0.818022],"study_design_scores_gemma":[0.0003560999,0.00002936126,0.01640349,0.000005577414,0.000007776668,0.000004277882,0.000008843033,0.9613779,0.002411214,0.00006148137,0.01918724,0.0001467027],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.207831,0.0000300553,0.7893299,0.0004218932,0.0001800567,0.0001041894,5.475339e-7,0.0001453801,0.001957019],"genre_scores_gemma":[0.9970557,0.000007320993,0.002355882,0.000164827,0.0001225947,0.00001889054,0.000005420433,0.000002949675,0.0002663973],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9612902,"threshold_uncertainty_score":0.1806471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006765194173599514,"score_gpt":0.2023048387945377,"score_spread":0.1955396446209381,"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."}}