{"id":"W1860007637","doi":"10.1007/978-3-319-15657-6_15","title":"Modeling Network Traffic","year":2015,"lang":"en","type":"book-chapter","venue":"","topic":"Network Traffic and Congestion Control","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Burstiness; Traffic generation model; Autocorrelation; Computer science; Traffic congestion reconstruction with Kerner's three-phase theory; Traffic flow (computer networking); Computer network; Network packet; Real-time computing; Traffic congestion; Statistics; Mathematics; Engineering","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003314948,0.0003454366,0.0003928302,0.00006789503,0.00009196495,0.0001522995,0.00102702,0.0003240181,0.0002236734],"category_scores_gemma":[0.000004372118,0.0003122886,0.0001681611,0.00004590232,0.00002741911,0.0001699238,0.0001944236,0.0003946969,0.0008592354],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006043138,"about_ca_system_score_gemma":0.0002361472,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001574244,"about_ca_topic_score_gemma":0.00002153281,"domain_scores_codex":[0.9982381,0.0000159581,0.000349758,0.0005807935,0.0004369701,0.0003783858],"domain_scores_gemma":[0.9986829,0.00004597662,0.00008487107,0.0007530462,0.0002006891,0.0002325092],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001646587,0.000001819395,1.3311e-8,0.000001264398,0.00001752354,0.000008934704,0.000008297578,0.3429637,6.740522e-9,0.4207702,0.0279432,0.2082834],"study_design_scores_gemma":[0.000157048,0.00002729761,1.136716e-8,0.00004078028,0.00001593786,0.00001081174,6.035273e-7,0.7136912,7.894249e-9,0.03158399,0.2541991,0.0002732022],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[8.291325e-7,0.002293873,0.4803754,0.0003579695,0.0007522909,0.0001207564,6.822431e-7,0.0005062834,0.5155919],"genre_scores_gemma":[0.01138311,0.0001416043,0.01506229,0.0007553289,0.001913895,0.00001054482,0.00001074326,0.00004989886,0.9706726],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4653131,"threshold_uncertainty_score":0.9999329,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03880401819266802,"score_gpt":0.2259909821433199,"score_spread":0.1871869639506519,"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."}}