{"id":"W1674221619","doi":"10.1109/itc.2015.19","title":"On Optimal Control for Energy-Aware Queueing Systems","year":2015,"lang":"en","type":"article","venue":"","topic":"Green IT and Sustainability","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Computer science; Provisioning; Context (archaeology); Queueing theory; Markov decision process; Set (abstract data type); Markov process; Mathematical optimization; Work (physics); Control (management); Optimal control; Distributed computing; Energy (signal processing); Operations research; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001501807,0.00008814796,0.0001302825,0.00003054327,0.00002252339,0.00003018148,0.00006482999,0.00005476982,0.000007716247],"category_scores_gemma":[0.00002783004,0.00007460143,0.00004106878,0.00003622426,0.000007766367,0.00005811381,0.000005591849,0.00003831844,0.000007151192],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001131181,"about_ca_system_score_gemma":0.00002025006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001499265,"about_ca_topic_score_gemma":0.00002040193,"domain_scores_codex":[0.9995012,0.00001183176,0.0001152568,0.00009491199,0.000083091,0.0001937306],"domain_scores_gemma":[0.9995956,0.00007280661,0.000007947042,0.0001388446,0.00008942877,0.0000953396],"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":[0.00009611204,0.00003197826,0.000722374,0.000217519,0.0000655262,0.0000111384,0.0002315492,0.8654734,0.00005251098,0.0950625,0.0348497,0.003185644],"study_design_scores_gemma":[0.0008552779,0.00008909878,0.0000297624,0.00000823376,0.000007081895,0.00000167493,0.0005412943,0.9848243,0.0001482443,0.0006936931,0.0126735,0.0001278477],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08328106,0.0001615304,0.9016868,0.00006852241,0.0006077537,0.0002868263,0.00001021418,0.0004721299,0.0134252],"genre_scores_gemma":[0.9984786,3.885149e-7,0.0001540049,0.00003315666,0.0001019495,0.00007247936,0.000003814543,0.00001784008,0.001137787],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9151976,"threshold_uncertainty_score":0.3042158,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01121752185604158,"score_gpt":0.206801261147555,"score_spread":0.1955837392915134,"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."}}