{"id":"W2403863631","doi":"10.1145/2901739.2901763","title":"GreenOracle","year":2016,"lang":"en","type":"article","venue":"","topic":"Green IT and Sustainability","field":"Engineering","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates - Technology Futures","keywords":"Energy consumption; Computer science; Software; Embedded system; Consumption (sociology); Instrumentation (computer programming); Energy (signal processing); Software engineering; Operating system; Engineering; Electrical engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00002915082,0.00002813185,0.00002833115,0.00001019626,0.000007904543,0.000002905264,0.00003455188,0.00001448109,0.0005932694],"category_scores_gemma":[0.000007476049,0.00001579501,0.0000131431,0.00002738912,0.000009483643,0.00005075135,0.000006330849,0.00001092302,0.0002252384],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002079512,"about_ca_system_score_gemma":0.000002153232,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006430263,"about_ca_topic_score_gemma":0.00001589951,"domain_scores_codex":[0.9998125,0.0000015924,0.00003688127,0.00003577456,0.00002787041,0.00008531599],"domain_scores_gemma":[0.9998566,0.00001263119,0.000001159205,0.00009376893,0.00001074064,0.00002512371],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000005037157,0.00001865363,0.120739,0.00005067464,0.00002126447,0.00001121279,0.000120184,0.0000789848,0.01877662,0.01592839,0.03774468,0.8065053],"study_design_scores_gemma":[0.001170921,0.00006953701,0.403258,0.00001900866,0.000009695256,0.000008477786,0.000217439,0.003462702,0.05257351,0.04690132,0.491603,0.0007063225],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8666238,0.00002407736,0.02224475,0.0003233424,0.00009224973,0.00003655883,7.835198e-7,0.0004871623,0.1101673],"genre_scores_gemma":[0.996146,0.000002289508,0.0001457003,0.0000123774,0.00002029258,0.000001988398,6.856479e-8,0.000004845269,0.003666477],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.805799,"threshold_uncertainty_score":0.6495884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003156344801724889,"score_gpt":0.1567500805610166,"score_spread":0.1535937357592917,"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."}}