{"id":"W1993274576","doi":"10.1002/dac.496","title":"A simple, scalable and provably stable explicit rate computation scheme for flow control in communication networks","year":2001,"lang":"en","type":"article","venue":"International Journal of Communication Systems","topic":"Network Traffic and Congestion Control","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nortel (Canada)","funders":"","keywords":"Computer science; Scalability; Computation; Controller (irrigation); Simple (philosophy); Flow control (data); Process (computing); Scheme (mathematics); Control (management); Algorithm; Control theory (sociology); Computer network; 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":[0.002342059,0.0001445359,0.0003254353,0.000270585,0.0001394659,0.0004794838,0.001475248,0.00008796468,0.000003033809],"category_scores_gemma":[0.0001144807,0.0001405719,0.00007545076,0.0002734854,0.00004449317,0.001119285,0.0001351886,0.000261566,0.000002503911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001452056,"about_ca_system_score_gemma":0.0001041478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006374135,"about_ca_topic_score_gemma":0.00004768657,"domain_scores_codex":[0.9978048,0.0005258927,0.0009577626,0.0001688675,0.0003433449,0.0001993419],"domain_scores_gemma":[0.9962093,0.000967935,0.000866271,0.0004614832,0.001406978,0.0000880389],"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":[0.0004602398,0.0002499867,0.007813804,0.000009354582,0.000243951,0.000009313281,0.0005818522,0.837966,0.0001827535,0.053842,0.003347164,0.09529357],"study_design_scores_gemma":[0.003196706,0.00007015424,0.001689801,0.0002029677,0.00001058604,0.00007959398,0.000147226,0.9783935,0.000004379257,0.001528052,0.01454967,0.0001273982],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01481622,0.00533547,0.9748632,0.003724304,0.0003886387,0.0005395215,0.000004596529,0.00003999172,0.0002880988],"genre_scores_gemma":[0.984217,0.001447272,0.01363986,0.000360346,0.0001349791,0.00008972876,0.00002268584,0.00001257375,0.00007547838],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9694009,"threshold_uncertainty_score":0.5732358,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0164899866431664,"score_gpt":0.2715358232506895,"score_spread":0.2550458366075231,"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."}}