{"id":"W2159743267","doi":"10.1109/tnet.2007.896507","title":"Distributed Rate Allocation for Inelastic Flows","year":2007,"lang":"en","type":"article","venue":"IEEE/ACM Transactions on Networking","topic":"Network Traffic and Congestion Control","field":"Computer Science","cited_by":142,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Air Force Office of Scientific Research; Defense Advanced Research Projects Agency; California Institute of Technology; University of Toronto; Purdue University; Yonsei University; National Science Foundation","keywords":"Mathematical optimization; Computer science; Heuristics; Limit (mathematics); Maximization; Utility maximization; Rate of convergence; Provisioning; Utility maximization problem; Convergence (economics); Mathematical economics; Mathematics; Economics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007974697,0.0002203919,0.0002046571,0.0001413377,0.0004613138,0.0001435659,0.0006579819,0.0001250712,0.000009588955],"category_scores_gemma":[0.0000210437,0.0002252445,0.000149461,0.0006808635,0.00002998853,0.0002628454,0.000005574946,0.0002525399,0.00003195457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001022162,"about_ca_system_score_gemma":0.00006502528,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005117638,"about_ca_topic_score_gemma":0.0001123702,"domain_scores_codex":[0.9983025,0.00006501727,0.0003999658,0.0004704398,0.0002041179,0.0005579796],"domain_scores_gemma":[0.9979225,0.00105047,0.0001149112,0.0006156269,0.0001402123,0.0001563042],"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":[0.00007820316,0.00007547703,0.000009020078,0.000006785729,0.00004355637,0.000004598171,0.00006956494,0.2723538,0.0001923765,0.001491124,0.0003127629,0.7253627],"study_design_scores_gemma":[0.001100412,0.0001905646,0.0001879075,0.00007599926,0.00004934258,0.00001131138,0.00001712373,0.9702513,0.0005041828,0.001794326,0.02548935,0.0003282515],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002290294,0.000104966,0.9916437,0.0009727375,0.003962386,0.0004507182,0.000008984761,0.0004625267,0.0001036927],"genre_scores_gemma":[0.9769107,0.00002487737,0.0214583,0.000484069,0.0008128597,0.0001002286,0.0000155286,0.00002236727,0.0001710926],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9746204,"threshold_uncertainty_score":0.9185204,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02166859084377924,"score_gpt":0.2531395800328795,"score_spread":0.2314709891891003,"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."}}