{"id":"W4200388228","doi":"10.1364/jocn.443448","title":"RIFL: a reliable link layer network protocol for data center communication","year":2021,"lang":"en","type":"article","venue":"Journal of Optical Communications and Networking","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Division of Electrical, Communications and Cyber Systems; Natural Sciences and Engineering Research Council of Canada; Xilinx","keywords":"Data link layer; Computer network; Computer science; Link layer; Protocol (science); Layer (electronics); Network layer; Link (geometry); Application layer; Center (category theory); Physical layer; Telecommunications; Operating system; Network packet","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001636969,0.0001035083,0.0002206553,0.00004063555,0.00051992,0.000352742,0.002735353,0.00006019772,0.000002267414],"category_scores_gemma":[0.00005794721,0.00008718921,0.00007490033,0.0003161828,0.00007587623,0.0001019585,0.003874922,0.0003925555,0.000001001856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002548912,"about_ca_system_score_gemma":0.00007092571,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002214317,"about_ca_topic_score_gemma":0.000007260148,"domain_scores_codex":[0.9986395,0.000185249,0.0005615544,0.0001897175,0.0001832965,0.0002407109],"domain_scores_gemma":[0.9958532,0.0006873951,0.0003379934,0.00271045,0.0003104363,0.0001005219],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008986105,0.0006943612,0.003570355,0.0001366859,0.0003144623,0.00001711622,0.0004524363,0.00632007,0.00004938393,0.1286441,0.0367105,0.8230006],"study_design_scores_gemma":[0.0005858376,0.0000603282,0.0001432195,0.0003197328,0.00001751263,0.00006402953,0.00001621163,0.4135265,0.0000040825,0.003306607,0.5818767,0.00007925087],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0004715379,0.005439376,0.9158333,0.05060603,0.0004380394,0.01512132,0.000002431931,0.00009656643,0.01199141],"genre_scores_gemma":[0.04330235,0.0005053809,0.9525262,0.0008661983,0.0007739217,0.001822749,0.00001302798,0.00001857117,0.0001715799],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8229214,"threshold_uncertainty_score":0.5083011,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1204092510368501,"score_gpt":0.358005811868296,"score_spread":0.2375965608314459,"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."}}