{"id":"W3101913426","doi":"","title":"A comparison of partitioning strategies in AC optimal power flow","year":2019,"lang":"en","type":"article","venue":"IEEE PES Innovative Smart Grid Technologies Conference","topic":"Optimal Power Flow Distribution","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Partition (number theory); Scalability; Benchmark (surveying); Computer science; Power flow; Mathematical optimization; Grid; Spectral clustering; Graph partition; Cluster analysis; Parallel computing; Power (physics); Algorithm; Electric power system; Graph; Mathematics; Theoretical computer science; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00121614,0.000878383,0.000787753,0.001141384,0.0005196589,0.0008510647,0.0007714145,0.0009128137,0.001399941],"category_scores_gemma":[0.004634993,0.0002757901,0.0003752729,0.001038557,0.0004812686,0.001124335,0.0006722067,0.0004871954,0.0002426387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007671626,"about_ca_system_score_gemma":0.0007347686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005015959,"about_ca_topic_score_gemma":0.005432645,"domain_scores_codex":[0.9992672,0.0003287281,0.00004259539,0.00008023128,0.0001849775,0.00009625468],"domain_scores_gemma":[0.9979772,0.001342643,0.0000974726,0.0002008665,0.000297875,0.00008401854],"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":[0.0007638028,0.0002799059,0.001230816,0.0003018956,0.00008639989,0.00005788573,0.0002041585,0.8044799,0.003774084,0.01376909,0.002216846,0.1728352],"study_design_scores_gemma":[0.00008526127,0.0005260169,0.00136478,0.00005866777,0.00004074652,0.00005487238,0.0002379591,0.9858164,0.003631923,0.005764488,0.002398731,0.00002014183],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6372087,0.007399144,0.31636,0.0006727026,0.0002104569,0.0003226852,0.0003408259,0.0009570648,0.03652838],"genre_scores_gemma":[0.9279493,0.001425267,0.0686818,0.00009861928,0.00002310244,0.0001165166,0.0003128885,0.0001276321,0.001264866],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005015959,"threshold_uncertainty_score":0.009973526,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02125913625258257,"score_gpt":0.2796835700562902,"score_spread":0.2584244338037076,"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."}}