{"id":"W2140021397","doi":"10.1109/milcom.1998.726930","title":"A framework of flow control in high-speed ATM wide area networks","year":2002,"lang":"en","type":"article","venue":"","topic":"Network Traffic and Congestion Control","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Computer network; Asynchronous Transfer Mode; Flow control (data); Queueing theory; ATM adaptation layer; Scheduling (production processes); Queuing delay; Statistical time division multiplexing; Multiplexing; Real-time computing; Distributed computing; Engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002975437,0.001366227,0.0009074892,0.0008898642,0.001736381,0.003267806,0.00312758,0.002403919,0.003109215],"category_scores_gemma":[0.002789353,0.0004802068,0.001346055,0.001218105,0.003964738,0.00452424,0.001689617,0.003945289,0.00106717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002032673,"about_ca_system_score_gemma":0.002563821,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003562807,"about_ca_topic_score_gemma":0.001926539,"domain_scores_codex":[0.9979387,0.0006585565,0.00009557568,0.0003945512,0.0007593878,0.0001532488],"domain_scores_gemma":[0.9989749,0.0004089596,0.00009079008,0.0001878412,0.0002445691,0.00009292307],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001764893,0.00003653552,0.00007525698,0.00008025355,0.00001545172,0.00007240575,0.0001072631,0.04336654,0.001552184,0.9333944,0.001649078,0.01963293],"study_design_scores_gemma":[0.0000419343,0.0001073932,0.0001292054,0.00008748699,0.00003081744,0.00008707314,0.00004075995,0.3808265,0.001408951,0.5840254,0.03317637,0.00003807747],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0009881824,0.001224343,0.9924358,0.0005367359,0.0001901701,0.00005771142,0.00004090417,0.0001573257,0.004368858],"genre_scores_gemma":[0.1889171,0.00507986,0.7949252,0.0006639608,0.001726847,0.0007307342,0.0002124313,0.0001101963,0.007633737],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003562807,"threshold_uncertainty_score":0.01573581,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0111031882026303,"score_gpt":0.1979058960438758,"score_spread":0.1868027078412454,"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."}}