{"id":"W2018148490","doi":"10.1109/ccdc.2011.5968279","title":"A guaranteed cost congestion control strategy for a network of multi-agent systems subject to differentiated services traffic","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":"Concordia University","funders":"","keywords":"Computer science; Network congestion; Network traffic control; Differentiated services; MATLAB; Controller (irrigation); Linear matrix inequality; Traffic congestion; Computer network; Distributed computing; Mathematical optimization; Engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007136565,0.0007898539,0.0005960052,0.0003276324,0.0004870658,0.0008950615,0.001174265,0.0006994868,0.0008813567],"category_scores_gemma":[0.001019279,0.0001980847,0.0003666096,0.0002879792,0.0006758709,0.0007093378,0.0007279089,0.0008230578,0.00008667023],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001277667,"about_ca_system_score_gemma":0.001210946,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0051899,"about_ca_topic_score_gemma":0.004270513,"domain_scores_codex":[0.9995815,0.0001053011,0.00001643258,0.0001044814,0.0001301864,0.00006204097],"domain_scores_gemma":[0.9995264,0.0001553871,0.00009386671,0.00003005573,0.0001513858,0.0000428161],"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":[0.00007749983,0.00006011125,0.0003518825,0.0001101883,0.00003937048,0.0001786861,0.0001220381,0.9082348,0.01063651,0.03979357,0.001417001,0.03897827],"study_design_scores_gemma":[0.00000989712,0.00004488611,0.0000490406,0.000002412167,0.000006655051,0.00001140121,0.000005031771,0.9973572,0.0004698929,0.001623297,0.0004164944,0.000003795247],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01790843,0.0001714208,0.9796661,0.0001373961,0.0000642814,0.00004257713,0.00001714333,0.0001236384,0.001868998],"genre_scores_gemma":[0.9597617,0.000146275,0.03813844,0.00006535505,0.00005737122,0.00009076489,0.00003206127,0.00001941972,0.0016886],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0051899,"threshold_uncertainty_score":0.01031935,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04241970630024865,"score_gpt":0.2485003578479224,"score_spread":0.2060806515476737,"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."}}