{"id":"W1984896319","doi":"10.1016/j.ijepes.2009.03.015","title":"A new computational method for reactive power market clearing","year":2009,"lang":"en","type":"article","venue":"International Journal of Electrical Power & Energy Systems","topic":"Electric Power System Optimization","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University; University of New Brunswick","funders":"","keywords":"AC power; Market clearing; Clearing; Integer programming; Linear programming; Mathematical optimization; Computer science; Activity-based costing; Electricity market; Power market; Transformer; Deregulation; Electric power system; Power (physics); Electricity; Economics; Engineering; Voltage; Mathematics; Electrical engineering; Microeconomics; Finance","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":[0.0008273369,0.0007654428,0.00106913,0.0007888283,0.0008404796,0.001271318,0.002003806,0.001156969,0.01501611],"category_scores_gemma":[0.003239604,0.000587063,0.0008305768,0.0009957283,0.0005826954,0.001556701,0.001248954,0.001655985,0.002910987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004357946,"about_ca_system_score_gemma":0.001166956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004878347,"about_ca_topic_score_gemma":0.007977765,"domain_scores_codex":[0.9995139,0.0001313013,0.00002777864,0.00007017142,0.0002191673,0.00003776421],"domain_scores_gemma":[0.9988273,0.000576273,0.00006594972,0.0001674981,0.0002963401,0.00006666064],"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":[0.0002271424,0.000186169,0.0004818286,0.0002074371,0.0001078531,0.0001661985,0.0001105818,0.5897149,0.006697217,0.07111116,0.01337564,0.3176138],"study_design_scores_gemma":[0.00002085944,0.000008050787,0.00002393274,0.000003814651,0.000004489706,0.00001221922,0.000003761127,0.9930959,0.000315759,0.004289216,0.002217528,0.000004396699],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001293445,0.00004672833,0.9955402,0.00006369378,0.0001150031,0.00003159946,0.00004597261,0.0004513779,0.002412062],"genre_scores_gemma":[0.07011422,0.0001195759,0.9208712,0.0001407131,0.0001670291,0.000267663,0.0001971418,0.0006360806,0.007486389],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01501611,"threshold_uncertainty_score":0.0502339,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005274860693317346,"score_gpt":0.2492809838886087,"score_spread":0.2440061231952913,"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."}}