{"id":"W2157522295","doi":"10.1109/glocom.2003.1258815","title":"Simulation study of the effective bandwidth for multiclass Markovian sources in a partitioned buffer","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Markov process; Quality of service; Bandwidth (computing); Buffer overflow; Packet loss; Buffer (optical fiber); Markov chain; Multiplexing; Statistical time division multiplexing; Network packet; Heuristic; Queueing theory; Distributed computing; Algorithm; Real-time computing; Computer network; Mathematics; Statistics; Telecommunications; Artificial intelligence","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":[0.0003161613,0.00008550693,0.0001422653,0.0001171956,0.0001068429,0.00003126894,0.0001057314,0.0000238768,0.0000178782],"category_scores_gemma":[0.0003921351,0.00005774455,0.00006490474,0.0004133968,0.0000274103,0.0003705362,0.00005361543,0.00004331607,0.00000453612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000344513,"about_ca_system_score_gemma":0.000003493476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003911591,"about_ca_topic_score_gemma":0.002327539,"domain_scores_codex":[0.9994089,0.00002368954,0.0001873148,0.0001551907,0.0001116178,0.0001133082],"domain_scores_gemma":[0.9993584,0.0002526984,0.0001342091,0.000161591,0.00008984247,0.000003232149],"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":[0.0001327352,0.0003944995,0.04147165,0.00003444599,0.00003300232,3.608783e-7,0.000346252,0.952931,0.0002119078,0.003750055,0.000002063054,0.0006919843],"study_design_scores_gemma":[0.01112371,0.0001232183,0.2958824,0.000133942,0.0004018511,1.033529e-7,0.006576276,0.5667465,0.00165845,0.116393,0.0005290683,0.0004315184],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9786128,0.000003238616,0.01976451,0.0001666584,0.00004390577,0.001018742,5.203046e-7,0.00003201236,0.000357559],"genre_scores_gemma":[0.9994299,5.989683e-8,0.0001245841,0.0001915825,0.00007925894,0.00009484522,0.000002234173,0.00001042131,0.00006712512],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3861845,"threshold_uncertainty_score":0.2354754,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01110385350818928,"score_gpt":0.2541363525444318,"score_spread":0.2430324990362425,"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."}}