{"id":"W2544012095","doi":"10.1109/mascots.2014.14","title":"Turbocharged Speed Scaling: Analysis and Evaluation","year":2014,"lang":"en","type":"article","venue":"","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Alberta Innovates - Technology Futures","keywords":"Computer science; Scaling; Energy consumption; Scheduling (production processes); Turbocharger; Speedup; Turbo; Real-time computing; Parallel computing; Automotive engineering; Mathematical optimization; Engineering","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":[0.002364021,0.001045402,0.0007177971,0.00159117,0.0004557143,0.0009700995,0.001461921,0.0007364174,0.001575362],"category_scores_gemma":[0.007932723,0.0002462878,0.0004004761,0.00182512,0.0008010929,0.001537656,0.0005981412,0.0005522936,0.0003118707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001495959,"about_ca_system_score_gemma":0.0009709867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00401201,"about_ca_topic_score_gemma":0.002052336,"domain_scores_codex":[0.9981147,0.0003772367,0.0000661065,0.0001141537,0.001141965,0.0001857501],"domain_scores_gemma":[0.9947169,0.002742608,0.0003764828,0.000580792,0.001413496,0.0001697358],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001177664,0.0003452052,0.007253984,0.0004178291,0.00008768394,0.0002520294,0.0001193689,0.8182355,0.01974792,0.007153665,0.002380604,0.1428284],"study_design_scores_gemma":[0.00001541061,0.0002775626,0.001045232,0.000009030035,0.00001667623,0.0000677323,0.0000225303,0.9871587,0.01000402,0.0007227135,0.0006453958,0.00001503156],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7602037,0.002688084,0.209208,0.0004195611,0.0002238742,0.0005526067,0.0004360262,0.00431279,0.0219554],"genre_scores_gemma":[0.9810823,0.0004819127,0.01725107,0.00003462502,0.00002225203,0.00004961651,0.0001465597,0.000106229,0.0008254275],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00401201,"threshold_uncertainty_score":0.01250231,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01692954911902289,"score_gpt":0.2559784215171786,"score_spread":0.2390488723981557,"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."}}