{"id":"W2972123927","doi":"10.1109/globecom38437.2019.9013475","title":"Intelligent Active Queue Management Using Explicit Congestion Notification","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Network Traffic and Congestion Control","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Active queue management; Network congestion; Explicit Congestion Notification; Computer science; Computer network; Random early detection; Queue; Transport layer; Layer (electronics); Slow-start; Network packet","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002916924,0.0003246255,0.0003158399,0.0002052111,0.0000901402,0.0003255529,0.001149644,0.0002520349,0.00005673753],"category_scores_gemma":[0.000008461235,0.0003192706,0.0001415023,0.0002001193,0.00002266775,0.0002476299,0.001054276,0.0004343545,0.0003145269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003528548,"about_ca_system_score_gemma":0.0001337278,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006477157,"about_ca_topic_score_gemma":0.00001086293,"domain_scores_codex":[0.997794,0.0001214279,0.0004104784,0.0009801877,0.0003850997,0.0003087652],"domain_scores_gemma":[0.9980345,0.00008257908,0.0003059854,0.001276731,0.0002026072,0.00009759518],"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":[0.0000162177,0.00007300817,0.00002464845,0.00006485305,0.0001247493,0.000006052715,0.0002468032,0.1792863,0.00004385467,0.1960417,0.000458766,0.6236131],"study_design_scores_gemma":[0.0002145562,0.00002331286,0.0003609779,0.0001745634,0.00005730885,0.000004318583,0.0001036936,0.9925901,0.0004721686,0.002930623,0.002655715,0.0004126599],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006115402,0.000149904,0.9807436,0.0009257622,0.002697976,0.001155745,0.000003775947,0.00040704,0.007800725],"genre_scores_gemma":[0.9597745,0.0001754478,0.0368559,0.0003828278,0.0002108961,0.0001290996,0.0000346165,0.00002097429,0.002415763],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9536591,"threshold_uncertainty_score":0.9999259,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03821601991228505,"score_gpt":0.2718681435167886,"score_spread":0.2336521236045036,"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."}}