{"id":"W4407366780","doi":"10.1016/j.epsr.2025.111487","title":"Applications of the partial element equivalent circuit method in computational electromagnetics simulation: An overview","year":2025,"lang":"en","type":"article","venue":"Electric Power Systems Research","topic":"Electromagnetic Simulation and Numerical Methods","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Partial element equivalent circuit; Electromagnetics; Equivalent circuit; Finite element method; Element (criminal law); Electronic engineering; Computational electromagnetics; Computer science; Computational science; Applied mathematics; Mathematics; Electrical engineering; Engineering; Physics; Electromagnetic field; Structural engineering; Voltage; Political science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002255325,0.0001498408,0.0002890511,0.0005185353,0.0001237239,0.00005144029,0.0004520808,0.0001100311,0.00008013694],"category_scores_gemma":[0.0001580935,0.0001310922,0.0000722022,0.003918427,0.00004179079,0.00006174574,0.00005728008,0.0004887576,0.000007420096],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003301697,"about_ca_system_score_gemma":0.0002091386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005328736,"about_ca_topic_score_gemma":0.000006215635,"domain_scores_codex":[0.9964764,0.001245235,0.0006576995,0.0002891269,0.0007882527,0.0005432973],"domain_scores_gemma":[0.9977742,0.001302171,0.00005768504,0.0004734713,0.000310967,0.00008146045],"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":[0.00001951423,0.0001883478,0.0006835484,0.0002268788,0.00005339035,8.602894e-7,0.0001603101,0.9015464,0.008986065,0.05580182,0.0002960807,0.03203681],"study_design_scores_gemma":[0.0004246003,0.0002379416,0.00515989,0.00005501465,0.00001113301,0.000002426997,0.00003110433,0.9720717,0.001699299,0.005584487,0.01459311,0.0001292891],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01512852,0.01185294,0.9637378,0.0001957533,0.000256552,0.002043676,0.000006364903,0.0001107306,0.006667594],"genre_scores_gemma":[0.9975193,0.00008911002,0.001622164,0.00002869237,0.0000367733,0.0003195747,0.00000572742,0.00002136602,0.000357345],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9823907,"threshold_uncertainty_score":0.5345783,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08475400665818814,"score_gpt":0.4413423373297117,"score_spread":0.3565883306715235,"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."}}