{"id":"W2009035836","doi":"10.1109/tcsii.2007.892215","title":"Real-Time Dynamic Voltage Loop Scheduling for Multi-Core Embedded Systems","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Circuits and Systems II Analog and Digital Signal Processing","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":111,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Francis Xavier University","funders":"","keywords":"Computer science; Dynamic voltage scaling; Dynamic priority scheduling; Scheduling (production processes); Real-time computing; Energy consumption; Voltage; Parallel computing; Embedded system; Engineering; Mathematical optimization; Schedule; Operating system; Electrical engineering; 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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0006901659,0.0002670531,0.0003636264,0.0002781752,0.0009385668,0.001118758,0.0002095777,0.0001577797,5.284908e-7],"category_scores_gemma":[0.000007533015,0.0002428224,0.00007804057,0.0003332956,0.00007582493,0.0008231463,0.000006738653,0.0001619081,0.000001818442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005373554,"about_ca_system_score_gemma":0.0000721777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003150029,"about_ca_topic_score_gemma":0.000002808857,"domain_scores_codex":[0.9982383,0.00002550501,0.0005217513,0.0005661908,0.0002412663,0.0004069366],"domain_scores_gemma":[0.9990261,0.0001750061,0.0002035987,0.0001761861,0.0002141114,0.0002049769],"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":[0.00004633483,0.0004528737,0.00007545976,0.001101895,0.0001237527,0.00003462277,0.001930256,0.1464552,0.01312277,0.001868331,0.00003429036,0.8347542],"study_design_scores_gemma":[0.0004773601,0.0002027519,0.00001840905,0.0003947713,0.00001790079,0.00009009281,0.000200072,0.9978422,0.0002897353,0.00009854247,0.00005215331,0.0003160365],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01593941,0.0007453838,0.9816909,0.000008192932,0.0001548038,0.0004160276,0.00002320606,0.0004804533,0.0005415502],"genre_scores_gemma":[0.9945585,0.00003547462,0.004251106,0.00002056175,0.00004598092,0.00002580568,0.000006887521,0.00002440308,0.001031353],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.978619,"threshold_uncertainty_score":0.9999182,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03399654071696992,"score_gpt":0.2824211772753988,"score_spread":0.2484246365584289,"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."}}