{"id":"W4392412513","doi":"10.1109/swc57546.2023.10449312","title":"Profiling and Understanding CPU Power Management in Linux","year":2023,"lang":"en","type":"article","venue":"","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Francis Xavier University","funders":"","keywords":"Profiling (computer programming); Operating system; Computer science; Power management; Embedded system; Power (physics); Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005156964,0.0003510882,0.0002772416,0.0007018075,0.0003256416,0.0008721066,0.0005368469,0.0002853596,0.0006405001],"category_scores_gemma":[0.004340181,0.0003063508,0.0001396045,0.0006324478,0.0004655393,0.001483568,0.0003372948,0.0005471504,0.0001875653],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006411735,"about_ca_system_score_gemma":0.0006017286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004121408,"about_ca_topic_score_gemma":0.003381063,"domain_scores_codex":[0.9994895,0.0001139023,0.00002924194,0.0001178501,0.0001741354,0.00007541419],"domain_scores_gemma":[0.9990989,0.0004228476,0.0001367487,0.0001733036,0.0001278626,0.00004034422],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0004037368,0.0002765928,0.05097166,0.0003091545,0.00003865129,0.0003282479,0.002190577,0.5853463,0.09029005,0.026085,0.00320301,0.240557],"study_design_scores_gemma":[0.00001057943,0.0001167155,0.01928764,0.00003043509,0.00001226118,0.00013066,0.0003165331,0.9434887,0.02221671,0.009951673,0.004406254,0.00003187009],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7317316,0.0006154464,0.2587758,0.0003621147,0.00003005716,0.00005175429,0.0002186168,0.002306636,0.005907931],"genre_scores_gemma":[0.9751296,0.0001888608,0.0239503,0.00003056739,0.000007162862,0.00002500788,0.0001073949,0.0001231186,0.0004378411],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004121408,"threshold_uncertainty_score":0.008194864,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04879196769259069,"score_gpt":0.2877854073728809,"score_spread":0.2389934396802902,"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."}}