{"id":"W4301235919","doi":"10.48550/arxiv.cs/0507004","title":"An End-to-End Probabilistic Network Calculus with Moment Generating\\n Functions","year":2005,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Network calculus; Computer science; Server; Probabilistic logic; Statistical time division multiplexing; Multiplexing; Queueing theory; Moment (physics); Theoretical computer science; Scalability; Algorithm; Calculus (dental); Computer network; Artificial intelligence; Quality of service; Telecommunications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004430573,0.0009059923,0.000770407,0.0008592485,0.001463362,0.003220038,0.002341322,0.00139143,0.003276757],"category_scores_gemma":[0.005464515,0.0006331507,0.001376877,0.001109521,0.002386444,0.004689386,0.00257324,0.003520006,0.0008881218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002368586,"about_ca_system_score_gemma":0.002445618,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002457109,"about_ca_topic_score_gemma":0.002362771,"domain_scores_codex":[0.9976633,0.000650421,0.000136494,0.000352724,0.0009439043,0.0002531082],"domain_scores_gemma":[0.9979619,0.001067337,0.0001630353,0.0002993518,0.0003630495,0.0001454199],"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":[0.00001881244,0.00001662823,0.00007295128,0.0000147455,0.000007582199,0.00006423038,0.0000671468,0.03886767,0.0008151843,0.9539592,0.000743761,0.005352073],"study_design_scores_gemma":[0.00001284867,0.00003396865,0.00006172623,0.00001117174,0.00001953587,0.00007582796,0.00001718634,0.5687155,0.001275845,0.4229211,0.006833233,0.00002205592],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002235207,0.00004751082,0.9941565,0.0001578435,0.0000403156,0.00002503045,0.00004668573,0.0001515442,0.003139369],"genre_scores_gemma":[0.3715872,0.0006142539,0.6104833,0.0003982784,0.0004032653,0.0003885473,0.0002208652,0.0002263308,0.01567791],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004430573,"threshold_uncertainty_score":0.02343142,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03614360997639721,"score_gpt":0.181907107592346,"score_spread":0.1457634976159488,"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."}}