{"id":"W3212804852","doi":"10.1109/iecon48115.2021.9589362","title":"Distributed Economic Dispatch over Strongly Connected Communication Networks","year":2021,"lang":"en","type":"article","venue":"","topic":"Electric Power System Optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Economic dispatch; Benchmark (surveying); Computer science; Electric power system; Telecommunications network; Distributed algorithm; Mathematical optimization; Control (management); Power (physics); Distributed computing; Computer network; Mathematics","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":[0.001321859,0.0009214081,0.0009190422,0.0005198751,0.000621264,0.001149478,0.000934203,0.001070245,0.001358127],"category_scores_gemma":[0.004213863,0.0003909589,0.0003047777,0.001099714,0.001104447,0.0017823,0.001325023,0.001283306,0.0001882747],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001008363,"about_ca_system_score_gemma":0.000685768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001512285,"about_ca_topic_score_gemma":0.001219538,"domain_scores_codex":[0.9989346,0.0005822692,0.0000342197,0.0001488632,0.0002179419,0.00008215161],"domain_scores_gemma":[0.9979866,0.001497691,0.000172947,0.00008708461,0.0001795529,0.00007619233],"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":[0.00004454797,0.0000108871,0.0001069834,0.00001572682,0.00000876627,0.00004035508,0.00001546304,0.9807413,0.0003955635,0.01273213,0.0002222707,0.005666013],"study_design_scores_gemma":[0.00001034634,0.000008352373,0.00002700489,8.601409e-7,0.000001026824,0.000003970199,0.00000372971,0.991064,0.0001012816,0.008655339,0.0001227417,0.000001438655],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0917195,0.0003377995,0.9020716,0.000526276,0.00006580847,0.00005363381,0.00005189308,0.0001060043,0.005067464],"genre_scores_gemma":[0.9622599,0.0003167102,0.0345198,0.00005222164,0.00004970418,0.00009966073,0.00006961873,0.00002422726,0.00260822],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001512285,"threshold_uncertainty_score":0.007316232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00390533302642488,"score_gpt":0.1883932624930105,"score_spread":0.1844879294665857,"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."}}