{"id":"W2053761086","doi":"10.1002/dac.1262","title":"UARA in edge routers: an effective approach to user fairness and traffic shaping","year":2011,"lang":"en","type":"article","venue":"International Journal of Communication Systems","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Concordia University; Polytechnique Montréal","keywords":"Computer science; Computer network; Provisioning; Network congestion; Quality of experience; Enhanced Data Rates for GSM Evolution; Quality of service; Traffic shaping; The Internet; Bandwidth (computing); Network traffic control; Peer-to-peer; Traffic congestion; Network packet; Telecommunications; World Wide Web","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001015964,0.00008522959,0.0001694273,0.0003629933,0.00004155338,0.0002391296,0.001684223,0.00003922124,5.973458e-7],"category_scores_gemma":[0.00003914275,0.00007703814,0.00004554515,0.000136737,0.00002317853,0.001065068,0.0002001439,0.000190926,0.000003628603],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001032373,"about_ca_system_score_gemma":0.00002698231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002094522,"about_ca_topic_score_gemma":0.00001641161,"domain_scores_codex":[0.9986979,0.0003533213,0.0004160384,0.0001310502,0.0003121414,0.00008948344],"domain_scores_gemma":[0.9987885,0.0001079414,0.0002662586,0.0003559977,0.000400978,0.0000803471],"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":[0.000874941,0.003260489,0.04331326,0.00006492223,0.0009603896,0.0001321876,0.1937215,0.07457609,0.003652416,0.3477511,0.0007909219,0.3309017],"study_design_scores_gemma":[0.004437123,0.0007475141,0.2205272,0.002004683,0.00003473328,0.001606412,0.00876964,0.756002,0.0003107314,0.001107066,0.003607237,0.0008456192],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7979288,0.0008497377,0.1989188,0.0002217654,0.0005746302,0.0001832886,0.000001211049,0.00002392167,0.001297929],"genre_scores_gemma":[0.9962032,0.00004746287,0.003536001,0.0001067303,0.00006385141,0.00001580707,0.000001407284,0.000005747868,0.00001979974],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6814259,"threshold_uncertainty_score":0.3141524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06499478482198469,"score_gpt":0.2824103312369798,"score_spread":0.2174155464149952,"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."}}