{"id":"W1555275600","doi":"10.1109/inm.2015.7140358","title":"Improving flow completion time for short flows in datacenter networks","year":2015,"lang":"en","type":"article","venue":"","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Cloud computing; Latency (audio); Computer network; Queue; Network congestion; Throughput; Real-time computing; Distributed computing; Operating system; Network packet; Wireless","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":[0.002958982,0.001162917,0.0008377008,0.00116417,0.00110769,0.0009999308,0.001859796,0.0005121644,0.001271797],"category_scores_gemma":[0.007391705,0.000337316,0.0003460703,0.0007548005,0.0006462873,0.001511876,0.0008940277,0.001288722,0.0002577741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002241968,"about_ca_system_score_gemma":0.002961456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01165789,"about_ca_topic_score_gemma":0.007102432,"domain_scores_codex":[0.9982571,0.0002244059,0.000104502,0.0003972335,0.000412282,0.0006044185],"domain_scores_gemma":[0.9950228,0.001434089,0.0006255807,0.0006650593,0.001175356,0.001077094],"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":[0.006175461,0.002636363,0.02156111,0.0002943082,0.0001340633,0.0003717736,0.0005317496,0.5221983,0.2030357,0.004292739,0.006274828,0.2324936],"study_design_scores_gemma":[0.0001477637,0.0007754733,0.004088775,0.0000141576,0.0000440978,0.00005951861,0.00007765667,0.9268088,0.06578883,0.0008497221,0.001299642,0.00004564999],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8806623,0.0006283838,0.1108012,0.0001932652,0.0001667497,0.0002020619,0.0001880282,0.005210553,0.001947548],"genre_scores_gemma":[0.975984,0.00007773241,0.02306615,0.00003293627,0.0000174065,0.00003516274,0.0001640711,0.0001194171,0.0005030944],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01165789,"threshold_uncertainty_score":0.02318007,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02653256006415454,"score_gpt":0.2400281197684241,"score_spread":0.2134955597042695,"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."}}