{"id":"W2051868991","doi":"10.1109/tdc.2010.5484276","title":"BC Hydro's experience on Voltage VAR Optimization in distribution system","year":2010,"lang":"en","type":"article","venue":"","topic":"Optimal Power Flow Distribution","field":"Engineering","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Hydro (Canada)","funders":"","keywords":"Voltage reduction; Smart grid; Metering mode; Energy conservation; Voltage; Voltage regulation; Computer science; Distribution (mathematics); Load management; Electrical engineering; Engineering; Mechanical 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":[0.0001170315,0.0001356604,0.0001121519,0.00005163661,0.00003838884,0.00004680219,0.0001265957,0.000123501,0.0001232525],"category_scores_gemma":[0.00003905571,0.0001383536,0.00002869686,0.000248392,0.00002177245,0.000235465,0.00001748112,0.0002178279,0.0001349518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002062954,"about_ca_system_score_gemma":0.000007042738,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000485995,"about_ca_topic_score_gemma":0.00002686334,"domain_scores_codex":[0.9992056,0.000009385092,0.0002123241,0.0001793017,0.0001625248,0.0002308172],"domain_scores_gemma":[0.9996354,0.0000200663,0.0000197236,0.0002305539,0.0000294686,0.00006477406],"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":[0.00001402274,0.00005218071,0.001124295,0.00005230418,0.000004948436,0.00001108213,0.0001292973,0.9654068,0.01640589,0.01529469,0.0008517603,0.0006527783],"study_design_scores_gemma":[0.0002443208,0.00002973173,0.00205632,0.0000293455,0.000002833837,0.000004881687,0.0001230441,0.9802058,0.01578506,0.000007882693,0.001320697,0.0001900697],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5448312,0.000005699525,0.4442856,0.00001653803,0.0007863073,0.0001858904,0.0000496352,0.0005898551,0.009249294],"genre_scores_gemma":[0.9987487,0.000002765554,0.0007991275,0.000007624795,0.00005621955,0.00003932591,0.0002868636,0.00001733504,0.00004210244],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4539174,"threshold_uncertainty_score":0.5641896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004535113095986792,"score_gpt":0.2024627002110381,"score_spread":0.1979275871150513,"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."}}