{"id":"W2100876404","doi":"10.1109/glocom.2010.5684172","title":"A Model for Steady State Throughput of TCP CUBIC","year":2010,"lang":"en","type":"article","venue":"","topic":"Network Traffic and Congestion Control","field":"Computer Science","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Vedecká Grantová Agentúra MŠVVaŠ SR a SAV","keywords":"CUBIC TCP; Throughput; Computer science; TCP acceleration; TCP global synchronization; Transmission Control Protocol; TCP Friendly Rate Control; Packet loss; Algorithm; Computer network; Network packet; Wireless; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001700711,0.00007334002,0.0001217338,0.00002807122,0.00004034722,0.00003335928,0.0004450748,0.00003476467,0.00001549554],"category_scores_gemma":[0.00001226622,0.00005920292,0.00005905359,0.00008884985,0.00003071813,0.0001938796,0.00005477491,0.00008110747,0.00001299221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003372755,"about_ca_system_score_gemma":0.00007823408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006248515,"about_ca_topic_score_gemma":0.0000834506,"domain_scores_codex":[0.9993405,0.000008824727,0.0001647705,0.0001946455,0.0001159855,0.0001753158],"domain_scores_gemma":[0.9993359,0.00009199127,0.00005802086,0.0003481551,0.0001110075,0.00005496054],"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":[0.00001362706,0.00006118028,0.00003763294,0.00000866527,0.00001707189,5.040861e-7,0.0004602013,0.01259502,0.001961899,0.5704709,0.004405485,0.4099678],"study_design_scores_gemma":[0.0004316689,0.00003686332,0.00002110432,0.000002284552,0.000003418263,0.000001269292,0.000004865312,0.983376,0.0003573142,0.0138251,0.001864818,0.00007524123],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02131378,0.00001726652,0.9745178,0.0007851467,0.0003003858,0.0001874485,0.000003323914,0.0001166699,0.002758172],"genre_scores_gemma":[0.881133,0.000002970019,0.1139988,0.0003248138,0.00003770899,0.00002467707,6.015424e-7,0.000004609449,0.004472909],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.970781,"threshold_uncertainty_score":0.2414225,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02124505172614448,"score_gpt":0.2517912544371289,"score_spread":0.2305462027109844,"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."}}