{"id":"W3126033631","doi":"10.7287/peerj.preprints.1219v2","title":"On the impact of sampling frequency on software energy measurements","year":2015,"lang":"en","type":"article","venue":"","topic":"Green IT and Sustainability","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Energy consumption; Computer science; Software; Android (operating system); Energy (signal processing); Mobile device; Sampling (signal processing); Real-time computing; Telecommunications; Electrical engineering; Statistics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002681742,0.0007534893,0.0004255283,0.001634921,0.0005520707,0.0009888267,0.0008517377,0.0009453038,0.000976636],"category_scores_gemma":[0.03147525,0.0003213814,0.000435258,0.001927894,0.0005542099,0.001129658,0.0007088991,0.001020482,0.0005086683],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006746549,"about_ca_system_score_gemma":0.0004201771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003560225,"about_ca_topic_score_gemma":0.004232634,"domain_scores_codex":[0.9933535,0.001109979,0.0004129163,0.001027278,0.003740325,0.0003559714],"domain_scores_gemma":[0.9768798,0.01505689,0.00205846,0.002762151,0.003013023,0.0002296437],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001889537,0.0006155833,0.2156805,0.001111925,0.0004203025,0.001124178,0.002106232,0.06648833,0.1744763,0.004879981,0.004058027,0.5271491],"study_design_scores_gemma":[0.00007680128,0.001994795,0.2674439,0.000430953,0.0003138896,0.002718101,0.00107441,0.3710208,0.3324192,0.005347047,0.01695314,0.0002068647],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7964994,0.002263535,0.1901118,0.0007320396,0.000349319,0.0001474557,0.0006435562,0.002751623,0.006501203],"genre_scores_gemma":[0.9591978,0.0003314464,0.03865626,0.0001541292,0.00004786527,0.000063117,0.0003946412,0.0002266971,0.0009280005],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003560225,"threshold_uncertainty_score":0.01418263,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0836025342532793,"score_gpt":0.2798620268107303,"score_spread":0.196259492557451,"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."}}