{"id":"W3027654966","doi":"10.1007/s11277-020-07477-x","title":"Improving Throughput in Lossy Wired/Wireless Networks","year":2020,"lang":"en","type":"article","venue":"Wireless Personal Communications","topic":"Network Traffic and Congestion Control","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lakehead University","funders":"","keywords":"TCP global synchronization; Computer science; TCP acceleration; Zeta-TCP; H-TCP; Computer network; TCP Westwood; TCP Westwood plus; TCP Friendly Rate Control; CUBIC TCP; TCP tuning; HSTCP; Transmission Control Protocol; 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":[],"consensus_categories":[],"category_scores_codex":[0.0002848037,0.0002273073,0.0003076945,0.00006868057,0.0003811005,0.0002140202,0.003160827,0.0001289039,0.00001829096],"category_scores_gemma":[0.00003088867,0.0002427653,0.0001203464,0.0009003187,0.0001942325,0.000526013,0.0009091356,0.0006112275,0.00005074502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008106206,"about_ca_system_score_gemma":0.0001735644,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001123245,"about_ca_topic_score_gemma":0.000291208,"domain_scores_codex":[0.9981049,0.0002651331,0.0004154606,0.000490812,0.0002823307,0.0004414086],"domain_scores_gemma":[0.9978639,0.0003715788,0.0001578198,0.001271927,0.0001156273,0.0002191611],"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":[0.00002547567,0.0001823568,0.00183976,0.00001947125,0.00003817179,0.00001781037,0.004295308,0.002174314,0.000271313,0.1506141,0.001189087,0.8393328],"study_design_scores_gemma":[0.0005874264,0.00004269569,0.0007009557,0.00004057392,0.000008768288,0.000008036986,0.0002555006,0.9946845,0.00001038849,0.0001249315,0.003266885,0.0002693693],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04294232,0.002973663,0.8973098,0.05242433,0.0002560826,0.0004764669,0.000009097586,0.0006422382,0.002966022],"genre_scores_gemma":[0.9900796,0.0003777026,0.006149189,0.003016274,0.0001762043,0.00009408505,0.00001882849,0.00002177323,0.0000662902],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9925101,"threshold_uncertainty_score":0.9899683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03083782689586581,"score_gpt":0.2485904530730452,"score_spread":0.2177526261771794,"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."}}