{"id":"W799714031","doi":"10.7287/peerj.preprints.1219v1","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":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Energy consumption; Computer science; Android (operating system); Energy (signal processing); Software; Power consumption; Sampling (signal processing); Real-time computing; Open source; Power (physics); Telecommunications; Statistics; Electrical engineering; Engineering; Mathematics; Detector; 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":[0.0002190058,0.00009000552,0.00009123817,0.00003210338,0.0000201347,0.000008705507,0.0001083013,0.00003532392,0.0001061835],"category_scores_gemma":[0.0002424391,0.00005114312,0.00006637736,0.00008314203,0.00001353009,0.00003297109,0.000009479049,0.00006292528,0.000009218565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002053459,"about_ca_system_score_gemma":0.00003626108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007570311,"about_ca_topic_score_gemma":0.0000426154,"domain_scores_codex":[0.9994671,0.0000209941,0.0001092122,0.00007278215,0.0001841147,0.0001457602],"domain_scores_gemma":[0.9995244,0.00006221384,0.00001242942,0.0002477806,0.00009410854,0.00005905714],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001295122,0.0003730803,0.252377,0.0001154761,0.0004749922,0.000005949294,0.001802085,0.6399692,0.002741569,0.04700475,0.02877333,0.02623304],"study_design_scores_gemma":[0.004084716,0.00397359,0.3346863,0.0003134483,0.00009090588,0.00000742363,0.00236899,0.04021225,0.05135377,0.5593764,0.001291364,0.00224088],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.962052,0.00004382959,0.01216622,0.00002575605,0.00009312618,0.00007277118,0.000003347494,0.0001282352,0.02541471],"genre_scores_gemma":[0.9995629,7.258868e-7,0.0003146534,0.00002091415,0.00001881752,0.000005089216,0.000001588478,0.00001127421,0.00006403677],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.599757,"threshold_uncertainty_score":0.2085556,"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."}}