{"id":"W3178865964","doi":"10.1109/mcom.001.2001070","title":"Hyperscale Data Center Networks with Transparent HyperX Architecture","year":2021,"lang":"en","type":"article","venue":"IEEE Communications Magazine","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Data center; Scalability; Computer network; Server; Architecture; Latency (audio); Cloud computing; Network topology; Distributed computing; Telecommunications; Database; Operating system","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":[0.0001795576,0.0001952598,0.000226426,0.0000563323,0.000292997,0.0001818195,0.004875768,0.00007191233,0.00002565763],"category_scores_gemma":[0.00002113111,0.0001647239,0.0000538065,0.0007640418,0.0001425852,0.0003114991,0.00116056,0.0004456961,0.00005053657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002598281,"about_ca_system_score_gemma":0.0001004203,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000972972,"about_ca_topic_score_gemma":0.0004886033,"domain_scores_codex":[0.9984723,0.0001836195,0.0002624544,0.000518022,0.0002250833,0.0003385433],"domain_scores_gemma":[0.9907091,0.0002740394,0.00007811346,0.008656234,0.0001511732,0.0001313939],"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":[0.0001151351,0.005015071,0.01549321,0.00008738942,0.0007657793,0.0002779562,0.001854738,0.1148122,0.0008440463,0.01843435,0.2084988,0.6338012],"study_design_scores_gemma":[0.00158226,0.00008744327,0.005333818,0.0001413814,0.00006718326,0.000414571,0.00002633239,0.3399325,0.00007500847,0.0005205006,0.651255,0.0005641013],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0006123654,0.004237135,0.9774523,0.01218482,0.0003763298,0.0001598584,0.0000647591,0.0003068942,0.004605589],"genre_scores_gemma":[0.5388536,0.002783148,0.4534513,0.002574942,0.0003008152,0.00006292577,0.00102443,0.00005233046,0.0008964678],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6332371,"threshold_uncertainty_score":0.9060472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06353403529581397,"score_gpt":0.2799757592976053,"score_spread":0.2164417240017913,"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."}}