{"id":"W2280777361","doi":"10.1109/pica.1999.779405","title":"Optimal power flow by a nonlinear complementarity method","year":2003,"lang":"en","type":"article","venue":"","topic":"Optimal Power Flow Distribution","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Universidade Federal de Pernambuco; Natural Sciences and Engineering Research Council of Canada; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Nonlinear system; Power flow; Mathematics; Nonlinear complementarity problem; Complementarity (molecular biology); Complementarity theory; Newton's method; Applied mathematics; Mathematical optimization; Mathematical analysis; Power (physics); Control theory (sociology); Electric power system; Computer science; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0008152556,0.0006914921,0.0007404027,0.0007127095,0.0005192737,0.0007007769,0.0007207432,0.0008442413,0.00587654],"category_scores_gemma":[0.001533155,0.0004224289,0.0006894332,0.000638045,0.0008804107,0.0007978612,0.0009056734,0.001213064,0.001085316],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008044461,"about_ca_system_score_gemma":0.001447481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005619355,"about_ca_topic_score_gemma":0.003587132,"domain_scores_codex":[0.9995658,0.0001804306,0.00001335807,0.00005193894,0.0001603905,0.00002811923],"domain_scores_gemma":[0.999642,0.0001822335,0.00002825256,0.00002607567,0.0001043034,0.00001719866],"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":[0.00004392772,0.00003305631,0.0001489979,0.0001323511,0.00002122557,0.0000540846,0.00007962738,0.8104905,0.002910387,0.09275366,0.003573392,0.08975871],"study_design_scores_gemma":[0.000009216482,0.00001154517,0.000026137,0.000009928018,0.000003389154,0.00001163721,0.000005268283,0.9848427,0.0004308412,0.01030953,0.004334717,0.00000509352],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0006510128,0.00006611218,0.9962701,0.00005678751,0.00002705606,0.00002240294,0.00001540799,0.00007783407,0.00281327],"genre_scores_gemma":[0.1219215,0.0005044678,0.863704,0.0001263398,0.0001033788,0.0004714887,0.00009800084,0.0001875703,0.01288327],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00587654,"threshold_uncertainty_score":0.01965898,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00944724076140009,"score_gpt":0.2570739197787281,"score_spread":0.247626679017328,"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."}}