{"id":"W2344774798","doi":"10.1109/jsyst.2015.2498639","title":"A Two-Way Street: Green Big Data Processing for a Greener Smart Grid","year":2016,"lang":"en","type":"article","venue":"IEEE Systems Journal","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"Pfizer (Canada); University of Toronto","funders":"Schlumberger Foundation","keywords":"Big data; Smart grid; Context (archaeology); Renewable energy; Variety (cybernetics); Computer science; Grid; Efficient energy use; Data science; Engineering; Telecommunications; Electrical engineering; Operating system; Artificial intelligence","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":[0.004343291,0.001074751,0.0007523656,0.001411062,0.00333632,0.01263515,0.001774407,0.004075794,0.00710667],"category_scores_gemma":[0.004294742,0.0007171329,0.001072188,0.002680217,0.004172063,0.02523221,0.007206747,0.008192465,0.002445499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001863664,"about_ca_system_score_gemma":0.004011604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001486314,"about_ca_topic_score_gemma":0.002594984,"domain_scores_codex":[0.9974709,0.0006825868,0.0001067964,0.0003222018,0.001010337,0.0004072184],"domain_scores_gemma":[0.9967352,0.0007842414,0.0001922272,0.0007887861,0.0007363821,0.0007632491],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003425958,0.0003052444,0.002679672,0.0005155919,0.0001551261,0.000385642,0.001043255,0.01076177,0.006438753,0.6800693,0.1076484,0.1896547],"study_design_scores_gemma":[0.0000497926,0.0001563555,0.000940691,0.0003408803,0.00006455913,0.0003166573,0.001801237,0.03271173,0.006531337,0.6274969,0.3294894,0.0001005662],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03198007,0.01914717,0.5956491,0.2581875,0.006781115,0.0003967271,0.0004570827,0.003690386,0.08371087],"genre_scores_gemma":[0.3822019,0.02497504,0.5058416,0.04446086,0.004478615,0.0003644936,0.0006512986,0.001666297,0.03535989],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01263515,"threshold_uncertainty_score":0.02377415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0719702002732547,"score_gpt":0.2776573078256055,"score_spread":0.2056871075523509,"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."}}