{"id":"W1937465037","doi":"10.1109/mascot.2000.876447","title":"A performance comparison of monofractal and multifractal traffic streams","year":2002,"lang":"en","type":"article","venue":"","topic":"Network Traffic and Congestion Control","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Multifractal system; STREAMS; Computer science; Traffic generation model; Simulation; Fractal; Real-time computing; Computer network; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"simulation_or_modeling","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"medium","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"design_other","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001840366,0.0005043994,0.0005989205,0.002109068,0.0006742149,0.001211592,0.0007405024,0.0007233784,0.002582808],"category_scores_gemma":[0.009859654,0.0001648817,0.0002576716,0.001629751,0.0003588753,0.001695133,0.0008983185,0.0003643616,0.0004877016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001281183,"about_ca_system_score_gemma":0.0007668015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00374223,"about_ca_topic_score_gemma":0.002891803,"domain_scores_codex":[0.9988019,0.0002588859,0.00006517762,0.0001868575,0.0004890867,0.0001980181],"domain_scores_gemma":[0.9948415,0.001873678,0.0003368705,0.0005707238,0.001995581,0.00038162],"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":[0.009965603,0.001144041,0.03578362,0.0004583239,0.0002674617,0.0003707039,0.0006366333,0.2059548,0.05292669,0.01639185,0.006552599,0.6695477],"study_design_scores_gemma":[0.000116288,0.001256699,0.006867138,0.00004344446,0.00005054388,0.0002940436,0.000179553,0.969729,0.01607428,0.003048343,0.002284904,0.00005572095],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9020299,0.001214865,0.08539855,0.0003061318,0.0001283792,0.0001740755,0.0003517304,0.002766347,0.007629978],"genre_scores_gemma":[0.9751639,0.000280249,0.02289667,0.00004812614,0.00002948782,0.00005190546,0.0003016749,0.00005686691,0.001171051],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00374223,"threshold_uncertainty_score":0.009732902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01782424935918061,"score_gpt":0.2257541324114749,"score_spread":0.2079298830522943,"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."}}