{"id":"W1987581179","doi":"10.1109/tac.2013.2286756","title":"Energy-Aware Scheduling on Heterogeneous Processors","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Automatic Control","topic":"Advanced Queuing Theory Analysis","field":"Business, Management and Accounting","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Computer science; Server; Scheduling (production processes); Distributed computing; Real-time computing; Mathematical optimization; Computer network; Mathematics","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","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001512152,0.0002922462,0.0003463787,0.0004207002,0.0003523789,0.0002423001,0.0002538403,0.00008805344,0.001866098],"category_scores_gemma":[0.0000175985,0.0002620763,0.000224125,0.0004687952,0.00005036066,0.0007096851,0.000001553065,0.0001499986,0.001722335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000644432,"about_ca_system_score_gemma":0.00001601546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001299968,"about_ca_topic_score_gemma":0.0000531121,"domain_scores_codex":[0.9985507,0.00002871525,0.0003825368,0.0003653379,0.0003122307,0.0003604595],"domain_scores_gemma":[0.9990214,0.0001831255,0.0002131447,0.0004009382,0.0001508938,0.00003055569],"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":[0.00008106988,0.0004818359,0.00001390663,0.0001756996,0.0003791696,0.0000174331,0.00005165179,0.7126852,0.001363788,0.001233142,0.0001154925,0.2834016],"study_design_scores_gemma":[0.0009812673,0.00002994556,0.00001363203,0.0001073468,0.0002164661,0.000003292724,0.00006915633,0.9921585,0.001238577,0.004458593,0.0004119022,0.0003112963],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1236306,0.00001624279,0.8729669,0.0009200993,0.0003321461,0.0003762356,0.000004058496,0.0007893929,0.0009643608],"genre_scores_gemma":[0.9949535,0.000002135855,0.0002510287,0.003728394,0.0001949146,0.0003367581,0.000002790312,0.00005529687,0.0004752348],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8727159,"threshold_uncertainty_score":0.9999831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008826034222911944,"score_gpt":0.2157817414237364,"score_spread":0.2069557072008244,"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."}}