{"id":"W2087704633","doi":"10.1016/j.ijepes.2012.07.037","title":"Extending the Multi-Area Thévenin Equivalents method for parallel solutions of bulk power systems","year":2012,"lang":"en","type":"article","venue":"International Journal of Electrical Power & Energy Systems","topic":"Power System Optimization and Stability","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Solver; Computation; Computer science; Parallel computing; Thévenin's theorem; Power (physics); Electricity; Electric power system; Algorithm; Electrical engineering; 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":[0.001817527,0.0002312054,0.0004999322,0.0003081728,0.00008760024,0.00009157625,0.0006800959,0.0001474617,0.00002815795],"category_scores_gemma":[0.000330899,0.0001657682,0.0003547082,0.0002558562,0.00003810547,0.0003477842,0.00004785516,0.0002248956,0.000003033683],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003837975,"about_ca_system_score_gemma":0.00006593189,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006374693,"about_ca_topic_score_gemma":0.000002553056,"domain_scores_codex":[0.9970172,0.0002883296,0.001303894,0.0001460287,0.0007673031,0.0004772619],"domain_scores_gemma":[0.9975382,0.0006125632,0.0005623532,0.0002350662,0.0008541908,0.0001976254],"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":[0.0002799271,0.0007404164,0.002380321,0.00008965877,0.002327638,0.00001356702,0.001096298,0.8612767,0.006353419,0.1114405,0.01353297,0.0004685322],"study_design_scores_gemma":[0.002120874,0.0002462302,0.0009151175,0.0002940003,0.0001200024,0.0007473329,0.0003786516,0.8930042,0.0005717789,0.0001249088,0.1010192,0.0004577379],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001065025,0.009801748,0.9791866,0.00009190157,0.008423228,0.0002238531,0.00006056992,0.00004554085,0.001101544],"genre_scores_gemma":[0.9963614,0.00009856083,0.00286718,0.00002623608,0.0002010364,0.00004468407,0.000008081463,0.00003969344,0.0003530864],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9952964,"threshold_uncertainty_score":0.6759831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03683513722011086,"score_gpt":0.2995387388319874,"score_spread":0.2627036016118766,"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."}}