{"id":"W2126584218","doi":"10.1145/2678373.2665719","title":"SleepScale","year":2014,"lang":"en","type":"article","venue":"ACM SIGARCH Computer Architecture News","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Science Foundation","keywords":"Computer science; Power management; Workload; Exploit; Data center; Server; Power (physics); Variety (cybernetics); Power budget; Quality of service; Task (project management); Frequency scaling; Distributed computing; Reliability engineering; Real-time computing; Power control; Operating system; Computer network; Engineering; Computer security; Artificial intelligence","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":[0.0006060809,0.001382562,0.0004622803,0.0005743032,0.000435874,0.0009910869,0.002363892,0.0005141047,0.02013828],"category_scores_gemma":[0.002348692,0.0006640314,0.000621,0.0004414092,0.0004583935,0.001671903,0.001052134,0.001103876,0.003398376],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000569238,"about_ca_system_score_gemma":0.0008593251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002526841,"about_ca_topic_score_gemma":0.005250883,"domain_scores_codex":[0.9995654,0.00005541306,0.00002874868,0.0001305957,0.0001534495,0.00006636377],"domain_scores_gemma":[0.9990184,0.0003437587,0.00007492926,0.0003356551,0.0001434821,0.00008372941],"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":[0.003001875,0.001338476,0.02569604,0.002216883,0.0004750921,0.00087275,0.001403185,0.1554276,0.06777286,0.04211853,0.3322343,0.3674424],"study_design_scores_gemma":[0.0005534302,0.0009495561,0.009917199,0.0001423212,0.0001833487,0.0005727531,0.0002115796,0.7722905,0.06032765,0.01941711,0.1352615,0.000173112],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"software","genre_gemma":"empirical","genre_scores_codex":[0.2109584,0.001842875,0.2456626,0.000807607,0.000617834,0.0009142655,0.01125892,0.4324655,0.09547196],"genre_scores_gemma":[0.8321232,0.000907124,0.0987667,0.0008616301,0.000105213,0.0006749704,0.01357466,0.02133575,0.03165077],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02013828,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00845375235718684,"score_gpt":0.2191184189686967,"score_spread":0.2106646666115098,"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."}}