{"id":"W2131682084","doi":"10.1109/glocom.1999.830028","title":"Resource allocation issues for long-tailed LRD Internet WAN traffic","year":2003,"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 Toronto","funders":"","keywords":"Computer science; Bandwidth (computing); Multiplexing; Computer network; Bandwidth allocation; Homogeneous; Quality of service; Statistical time division multiplexing; Resource allocation; Computation; The Internet; Admission control; Mathematical optimization; Distributed computing; Mathematics; Algorithm; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003374406,0.0001273096,0.0001407164,0.00005589018,0.00007050602,0.0001565208,0.0004700904,0.00006303773,0.00008092391],"category_scores_gemma":[0.00005118659,0.0001107883,0.00007328126,0.0001781368,0.00002587585,0.0002031096,0.00002564226,0.00006919084,0.00008941542],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002573688,"about_ca_system_score_gemma":0.00004193847,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002620603,"about_ca_topic_score_gemma":0.00003566205,"domain_scores_codex":[0.9989434,0.00007939488,0.0002113014,0.0003532963,0.0001522053,0.0002603523],"domain_scores_gemma":[0.9992861,0.0001251853,0.00005698174,0.0003572198,0.00008548714,0.00008899201],"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":[0.00002008164,0.00008118425,0.0001509603,0.00001044132,0.00003015466,0.000002671995,0.000435277,0.00354952,0.00001689798,0.3276017,0.04541464,0.6226865],"study_design_scores_gemma":[0.0008534643,0.0001844218,0.0002088822,0.00002208737,0.00001439741,0.00001229228,0.00006714821,0.5911891,0.0006119739,0.0007060487,0.4058477,0.0002824685],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0154728,0.0003547081,0.9735968,0.004101997,0.0003019202,0.0003710453,4.932768e-7,0.0004137761,0.00538645],"genre_scores_gemma":[0.9631891,0.000007401603,0.01644782,0.0008138607,0.0001083913,0.00006890645,0.000006600617,0.00001024245,0.0193477],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.957149,"threshold_uncertainty_score":0.4517817,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01369660881236358,"score_gpt":0.2415153552805546,"score_spread":0.227818746468191,"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."}}