{"id":"W39121104","doi":"10.1371/journal.pone.0308571","title":"Forward Explicit Congestion Notification (FECN) for Datacenter Ethernet Networks","year":2007,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Network Traffic and Congestion Control","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer network; Computer science; Ethernet; Network congestion; Computer security; Network packet","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006957829,0.0001377042,0.0001844575,0.00006429133,0.0001153333,0.0001173731,0.0005145497,0.0001106378,0.00001605801],"category_scores_gemma":[0.00005750973,0.0001365812,0.00005532769,0.0001928322,0.00002203751,0.0003665808,0.0000620165,0.0001365765,0.00006195606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005092314,"about_ca_system_score_gemma":0.00002393327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004480428,"about_ca_topic_score_gemma":0.00002965263,"domain_scores_codex":[0.9986458,0.0000359093,0.0002823622,0.0004007933,0.0002627874,0.0003723347],"domain_scores_gemma":[0.9987215,0.0003124785,0.0001259866,0.0005350796,0.0001849089,0.0001200793],"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":[0.0002702483,0.001608128,0.002229965,0.0000652705,0.0003335762,0.000005776874,0.0003694292,0.002916718,0.003394703,0.1404209,0.007138516,0.8412467],"study_design_scores_gemma":[0.001132212,0.0001670471,0.001809124,0.00009623409,0.00007711948,0.000001956807,0.00001939797,0.9863139,0.001935928,0.0005955884,0.007563595,0.0002878505],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01642052,0.0002068527,0.980219,0.001457612,0.000239425,0.0007748054,0.000005502035,0.0002785176,0.0003977546],"genre_scores_gemma":[0.9626099,0.00004105908,0.03482201,0.000825748,0.0005891195,0.0001931507,0.00006515421,0.00001780611,0.0008360089],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9833972,"threshold_uncertainty_score":0.556962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04561736478124628,"score_gpt":0.2384070691109325,"score_spread":0.1927897043296863,"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."}}