{"id":"W2132443825","doi":"10.1109/infcom.2011.5934905","title":"The impact of link scheduling on long paths: Statistical analysis and optimal bounds","year":2011,"lang":"en","type":"article","venue":"","topic":"Network Traffic and Congestion Control","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Burstiness; Network calculus; Computer science; Scheduling (production processes); Network packet; Upper and lower bounds; Key (lock); Mathematical optimization; Computer network; Distributed computing; Quality of service; Mathematics","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":[0.0002928514,0.00008162373,0.0001414831,0.0000593414,0.0001135546,0.00009583595,0.0002714223,0.00003173957,0.00004384221],"category_scores_gemma":[0.00003295415,0.00004599658,0.00008472482,0.0002983693,0.00008432903,0.00009169571,0.00005765617,0.00008788174,0.000006244085],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001079793,"about_ca_system_score_gemma":0.00004615454,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008797159,"about_ca_topic_score_gemma":0.00002236067,"domain_scores_codex":[0.9992897,0.00005439413,0.0001661911,0.0001842012,0.0001314675,0.0001740708],"domain_scores_gemma":[0.9992093,0.000313493,0.00005514215,0.0002781509,0.00005877387,0.0000850867],"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":[0.00004986277,0.00005176953,0.01435157,0.000001565986,0.0004813486,0.00001086971,0.0002945389,0.005354145,0.000007782864,0.1843818,0.0000518143,0.7949629],"study_design_scores_gemma":[0.0001630334,0.0002736151,0.1273729,0.000003413187,0.00005434966,0.000002020213,0.00001398196,0.8714322,0.00002365906,0.0005835305,0.000009066015,0.00006831241],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1358648,0.00008190967,0.8623655,0.00008185429,0.00003705753,0.00004291739,0.000001406435,0.00003582522,0.001488708],"genre_scores_gemma":[0.9637516,0.00002189687,0.03606281,0.00003146876,0.00003031098,0.000002958815,6.65449e-7,0.000002528858,0.00009582727],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.866078,"threshold_uncertainty_score":0.1875686,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01645201216871926,"score_gpt":0.2608990088959178,"score_spread":0.2444469967271985,"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."}}