{"id":"W2510164385","doi":"10.1109/tsg.2016.2603421","title":"Assessing Benefits of Volt-Var Control Schemes Using AMI Data Analytics","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Smart Grid","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Volt; Computer science; Analytics; Data analysis; Control (management); Reliability engineering; Electrical engineering; Data mining; Engineering; Voltage; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001674246,0.0001825262,0.0002480056,0.0001600446,0.0001054143,0.0000397377,0.000250061,0.00009368105,0.00006589491],"category_scores_gemma":[0.00001012431,0.0001493514,0.00007835194,0.0002252659,0.0000509948,0.0005961506,0.00000221852,0.0001461469,0.00001219991],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005262624,"about_ca_system_score_gemma":0.00003139285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003286457,"about_ca_topic_score_gemma":0.00004985211,"domain_scores_codex":[0.9989643,0.00002276493,0.00032819,0.0002246568,0.0001919566,0.000268122],"domain_scores_gemma":[0.9990692,0.0001794503,0.00005697902,0.0005561159,0.00005807242,0.0000802159],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002252847,0.00008293587,0.0005509761,0.00008116214,0.0003141438,0.000004599442,0.00005662932,0.8387089,0.08448748,0.00009251454,0.0001844135,0.07541365],"study_design_scores_gemma":[0.001746743,0.00007049424,0.0005907035,0.0009051918,0.0003438125,0.00003076552,0.0000522923,0.707244,0.2814057,0.00002815477,0.006966508,0.0006156295],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2163434,0.0001262935,0.7811661,0.00002825449,0.001455918,0.00005315891,0.0003140452,0.0001536751,0.0003590659],"genre_scores_gemma":[0.9952904,0.00006652556,0.004321329,0.00002179729,0.0001998026,0.000002762475,0.000006915931,0.00004497731,0.00004549814],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.778947,"threshold_uncertainty_score":0.6090374,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06352765120851782,"score_gpt":0.2700866007136961,"score_spread":0.2065589495051782,"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."}}