{"id":"W4410859297","doi":"10.3390/electronics14112214","title":"A Systematic Review of Energy Efficiency Metrics for Optimizing Cloud Data Center Operations and Management","year":2025,"lang":"en","type":"review","venue":"Electronics","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cloud computing; Data center; Center (category theory); Computer science; Systematic review; Energy management; Systems engineering; Operations research; Data science; Industrial engineering; Operations management; Engineering management; Engineering; Energy (signal processing); Statistics; Mathematics; Operating system; Political science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004335479,0.001563873,0.002878352,0.009597312,0.0005560788,0.002170807,0.001680856,0.001477438,0.004858674],"category_scores_gemma":[0.01656803,0.0007139671,0.003252853,0.01052558,0.0006117293,0.002480435,0.001003471,0.001118294,0.0009267494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001890294,"about_ca_system_score_gemma":0.01087831,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006626916,"about_ca_topic_score_gemma":0.01605156,"domain_scores_codex":[0.9974323,0.0006770266,0.0007300714,0.0002642389,0.0008008002,0.00009561724],"domain_scores_gemma":[0.9892024,0.007357391,0.00139924,0.0001909487,0.001709742,0.0001401883],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"systematic_review","study_design_scores_codex":[0.00009992113,0.0000637284,0.0005642517,0.4267443,0.001286336,0.0001136588,0.0001695743,0.0008244029,0.0005383567,0.00340079,0.01480683,0.5513878],"study_design_scores_gemma":[0.00007677991,0.0003452199,0.003459329,0.4900895,0.008375783,0.0006625015,0.0003232749,0.0004230263,0.0008812477,0.003423822,0.4918425,0.00009702216],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0002127382,0.9981028,0.0003993764,0.0002923613,0.00009590964,0.00005711737,0.000177399,0.00001121731,0.00065116],"genre_scores_gemma":[0.001602872,0.9969255,0.0008648986,0.0002078908,0.00004629996,0.00007109635,0.0001454375,0.000005609365,0.0001304366],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.009597312,"threshold_uncertainty_score":0.02292848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02788429951933044,"score_gpt":0.3016171944021054,"score_spread":0.273732894882775,"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."}}