{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000530978,0.0003372272,0.0003433672,0.0002663042,0.0002869755,0.0003107825,0.004170143,0.00008509991,0.00001170971],"category_scores_gemma":[0.0001067924,0.0002765064,0.0002050722,0.0005398394,0.00008600191,0.0000311008,0.003632453,0.0004617137,0.0001954655],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003551969,"about_ca_system_score_gemma":0.00002644299,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004732365,"about_ca_topic_score_gemma":0.00001656451,"domain_scores_codex":[0.9971032,0.0003249284,0.0003561679,0.0009079085,0.0005907061,0.0007170589],"domain_scores_gemma":[0.9963386,0.0006325211,0.0001062349,0.002587689,0.00006055553,0.0002743663],"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":[0.000004905925,0.00006812353,0.00045717,0.00002215228,0.00003734682,0.00001550128,0.001045031,0.02017429,0.0000871771,0.00955058,0.008524694,0.960013],"study_design_scores_gemma":[0.0008235121,0.0004258986,0.003681969,0.00005716957,0.00001171779,0.00008264963,0.000006187206,0.5179278,0.0002907504,0.03321275,0.4428562,0.0006234171],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04454096,0.00004440106,0.9372787,0.01012953,0.0009144769,0.000238452,5.573675e-7,0.0008017178,0.006051246],"genre_scores_gemma":[0.5350736,0.000001876776,0.4567778,0.005948391,0.001587377,0.0000168193,0.000002826888,0.00003141421,0.0005599078],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9593896,"threshold_uncertainty_score":0.9999687,"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."}}