{"id":"W4401797345","doi":"10.1109/tmag.2024.3447621","title":"Partial Element Equivalent Circuit Based Parallel Electromagnetic Transient Simulation on GPU","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Magnetics","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; Transient (computer programming); Computer science; Equivalent circuit; Transient analysis; Finite element method; Computational electromagnetics; Parallel computing; Computational science; Electromagnetic field; Transient response; Physics; Electrical engineering; Voltage","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001945002,0.0003823745,0.0002642392,0.0003290808,0.0001194474,0.0001045889,0.0001544274,0.0001647751,0.002087758],"category_scores_gemma":[0.000007037854,0.0003938197,0.0002296143,0.0005829904,0.00005315537,0.00006736963,5.615498e-7,0.0005234529,0.0002534025],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001975639,"about_ca_system_score_gemma":0.00004765596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003378587,"about_ca_topic_score_gemma":0.00000356681,"domain_scores_codex":[0.9978111,0.0001337432,0.0005050273,0.0004466966,0.0005267783,0.0005766493],"domain_scores_gemma":[0.9988028,0.0005443961,0.00002224796,0.0003749476,0.00004420631,0.0002113958],"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":[0.00006297979,0.0001659425,6.622437e-7,0.00007985289,0.00003803097,0.00001194751,0.0001036325,0.85452,0.01439936,0.0001700076,0.0001737204,0.1302738],"study_design_scores_gemma":[0.0007465954,0.002630449,0.0001456905,0.00007030928,0.0001368274,0.000003256967,0.000007147554,0.9570034,0.02643817,0.0002540394,0.01214446,0.0004196503],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0241791,0.000467879,0.9700497,0.0003143371,0.001300443,0.0005407544,0.00002910305,0.0009715692,0.002147154],"genre_scores_gemma":[0.9929484,0.0001389528,0.005735214,0.0002851777,0.0001230798,0.0001263404,0.000009954632,0.00009953454,0.0005334067],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9687693,"threshold_uncertainty_score":0.9998513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02973230164342952,"score_gpt":0.2866567597049198,"score_spread":0.2569244580614903,"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."}}