{"id":"W2553567329","doi":"10.1145/3004295","title":"Smart Meter Data Analytics","year":2016,"lang":"en","type":"article","venue":"ACM Transactions on Database Systems","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Data analysis; Analytics; Smart meter; Big data; Data science; Data mining; Smart grid; Electrical 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":[0.0005697055,0.0001714684,0.0002367216,0.0001865957,0.0002192093,0.0001887553,0.002628636,0.00004723188,0.0001137846],"category_scores_gemma":[0.00007928043,0.000110633,0.00008588134,0.0005172396,0.0000426709,0.001324282,0.000133607,0.0001055584,0.0003835325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004240837,"about_ca_system_score_gemma":0.00004443786,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002707799,"about_ca_topic_score_gemma":0.000101991,"domain_scores_codex":[0.9982066,0.00009476695,0.0003734519,0.000659561,0.0003603356,0.0003053502],"domain_scores_gemma":[0.9939816,0.0002722472,0.000111737,0.005429799,0.00006633112,0.0001382933],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000709379,0.0006914103,0.0006766364,0.0001971984,0.001559205,0.0001632647,0.0003050104,0.002308672,0.01126798,0.02187157,0.02421414,0.936674],"study_design_scores_gemma":[0.001525545,0.0002804157,0.0002409517,0.0006426423,0.0003676093,0.0002031356,0.0002330248,0.5039417,0.003748482,0.0002647902,0.4873213,0.001230415],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.000291823,0.00009117746,0.9963562,0.001015862,0.000627715,0.0001161458,0.0008728725,0.000154044,0.0004741462],"genre_scores_gemma":[0.9443691,0.000110609,0.05168378,0.0001392655,0.0001462817,0.00002446976,0.0001161368,0.00002676311,0.003383645],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9446725,"threshold_uncertainty_score":0.4929662,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09289352135828077,"score_gpt":0.2750155793791962,"score_spread":0.1821220580209155,"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."}}