{"id":"W2250533127","doi":"10.7939/r3-qv6m-f341","title":"The Power of System Call Traces: Predicting the Software Energy Consumption Impact of Changes","year":2014,"lang":"en","type":"article","venue":"University of Alberta Library","topic":"Green IT and Sustainability","field":"Engineering","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Energy consumption; Profiling (computer programming); Software; Software system; System call; Tracing; Software development; System software; Embedded system; Operating system; Engineering","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":[0.00008761386,0.00007278943,0.0001403603,0.00003597115,0.0000750457,0.000005401635,0.0002408817,0.00005672958,0.00003770727],"category_scores_gemma":[0.00002438097,0.0000497536,0.00009391794,0.00007621008,0.0001320292,0.0001671553,0.00005592438,0.00005785087,5.676716e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002389292,"about_ca_system_score_gemma":0.00002471555,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001600633,"about_ca_topic_score_gemma":0.0003837839,"domain_scores_codex":[0.9995747,0.00006417037,0.00009856522,0.00006746813,0.00008385936,0.0001112137],"domain_scores_gemma":[0.9991094,0.0005211338,0.0000749727,0.0002334902,0.00002918885,0.0000317439],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003738795,0.00009033162,0.9158859,0.002567344,0.0007482772,0.000004625801,0.03969422,0.01396102,0.0005154166,0.01109853,0.005958144,0.009102269],"study_design_scores_gemma":[0.002265603,0.001009254,0.7909905,0.0009743655,0.000338754,0.00001705646,0.04119749,0.1323171,0.006705506,0.0004896532,0.02294724,0.0007474854],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995938,0.0001855447,0.0005542412,0.00007751006,0.00005174358,0.0000702752,0.000008929153,0.00004663683,0.003067113],"genre_scores_gemma":[0.9994876,0.00003834232,0.00005665992,0.000002118459,0.00001032841,1.116901e-7,0.000006201527,0.000007850691,0.0003907619],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1248955,"threshold_uncertainty_score":0.2419689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004033363380838767,"score_gpt":0.15648299724934,"score_spread":0.1524496338685012,"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."}}