{"id":"W2161884835","doi":"10.1109/ispa.2008.128","title":"Energy Optimal Scheduling on Multiprocessors with Migration","year":2008,"lang":"en","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":73,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Multiprocessor scheduling; Multiprocessing; Parallel computing; Scheduling (production processes); Schedule; Time complexity; Job shop scheduling; Regular polygon; Mathematical optimization; Algorithm; Flow shop scheduling; Mathematics; Operating system","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":[0.00005633129,0.00009225227,0.0000768097,0.00009204214,0.0001681127,0.00004605614,0.000296521,0.0000349398,0.000004005897],"category_scores_gemma":[0.000009100438,0.00006911276,0.00001981811,0.0002681459,0.00002466749,0.0002350865,0.00004033969,0.00005429963,0.00000991485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001447641,"about_ca_system_score_gemma":0.00004136009,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004451309,"about_ca_topic_score_gemma":0.00000654747,"domain_scores_codex":[0.9993194,0.00001965666,0.0001043742,0.0002444935,0.000176051,0.0001360402],"domain_scores_gemma":[0.9995692,0.00003047261,0.00004794415,0.0002221608,0.00008361816,0.00004662876],"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":[0.0000236032,0.0001260002,0.0008408258,0.000003743185,0.00001187684,0.00002600788,0.0006707464,0.9335297,0.000154366,0.05265537,0.001442294,0.01051547],"study_design_scores_gemma":[0.0001562837,0.0001514123,0.000142871,0.00001173625,6.633237e-7,0.00002665455,0.00000542239,0.9784839,0.01992482,0.00007416696,0.0008975219,0.0001245864],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03726479,0.00001656376,0.9569837,0.0003360304,0.00002542742,0.00003016989,7.308646e-8,0.0007373886,0.004605799],"genre_scores_gemma":[0.5241686,0.00001611566,0.4750316,0.0003000124,0.00001493172,0.00000439188,0.000001015438,0.000003474039,0.000459922],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4869038,"threshold_uncertainty_score":0.2818336,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01718374779244544,"score_gpt":0.2317946283652094,"score_spread":0.214610880572764,"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."}}