{"id":"W3204613820","doi":"10.1109/access.2021.3117763","title":"Next-Generation Data Center Network Enabled by Machine Learning: Review, Challenges, and Opportunities","year":2021,"lang":"en","type":"article","venue":"IEEE Access","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Huawei Technologies (Canada)","funders":"","keywords":"Computer science; Data center; Automation; Workload; Variety (cybernetics); Server; Network management; Process (computing); Big data; Computer security; Data science; Computer network; Artificial intelligence; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001066772,0.0006206784,0.0006978183,0.001365091,0.000313254,0.001353698,0.001160332,0.00123796,0.002010988],"category_scores_gemma":[0.001884778,0.0003292698,0.0004445013,0.002458708,0.0005024356,0.003234702,0.0006796586,0.001343675,0.0009506082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005364955,"about_ca_system_score_gemma":0.001109808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001253941,"about_ca_topic_score_gemma":0.001239955,"domain_scores_codex":[0.9996318,0.00008543285,0.0000375599,0.0000693761,0.0001362823,0.00003949065],"domain_scores_gemma":[0.9986571,0.0008426699,0.00009313425,0.00004168325,0.0002975332,0.00006796753],"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":[0.00005816665,0.0001048327,0.0009000392,0.007705476,0.00008770882,0.0001469376,0.0001003396,0.004723391,0.0006767933,0.02440999,0.02661647,0.9344699],"study_design_scores_gemma":[0.00001778191,0.0002779294,0.001810334,0.005226434,0.0002247982,0.001085354,0.0002868257,0.01511003,0.001338619,0.02514288,0.9493881,0.00009094032],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0007244801,0.9906584,0.003560321,0.001456523,0.0005241476,0.000009898758,0.0000203416,0.00003279136,0.003013038],"genre_scores_gemma":[0.007777897,0.9881671,0.001889925,0.0005049988,0.0009586419,0.00001213557,0.00004773753,0.000007683073,0.0006338376],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002010988,"threshold_uncertainty_score":0.006727457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.20674535350467,"score_gpt":0.3070042295263044,"score_spread":0.1002588760216344,"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."}}