{"id":"W2099181948","doi":"10.1109/ccece.2012.6334886","title":"Electromagnetic transient simulation of large-scale electrical power networks using graphics processing units","year":2012,"lang":"en","type":"article","venue":"","topic":"Real-time simulation and control systems","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Graphics processing unit; Graphics; Central processing unit; Transient (computer programming); General-purpose computing on graphics processing units; CUDA; Parallel processing; Computational science; Parallel computing; Power (physics); Computer hardware; Computer graphics (images); Operating system","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009751862,0.0003473882,0.000280726,0.0002191291,0.0002295213,0.000494034,0.0003837578,0.0004369196,0.002497768],"category_scores_gemma":[0.0005958232,0.00014976,0.0003006525,0.0004335433,0.0002939325,0.0007491658,0.0003224952,0.0004531864,0.0003502991],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002242765,"about_ca_system_score_gemma":0.0002242923,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001364587,"about_ca_topic_score_gemma":0.001216088,"domain_scores_codex":[0.9999001,0.00003927666,0.000005017244,0.00001144179,0.000034631,0.000009441143],"domain_scores_gemma":[0.9998347,0.00009781778,0.0000130754,0.00002271361,0.00002147497,0.00001019426],"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":[0.000122414,0.00004648624,0.001451669,0.00008677612,0.00003255446,0.0003675251,0.0001000141,0.915122,0.02413457,0.01481443,0.002115032,0.04160653],"study_design_scores_gemma":[0.000009206222,0.00002430135,0.0002538115,0.000005066018,0.000003765851,0.0000547862,0.0000144107,0.990123,0.004100907,0.002352227,0.003053734,0.000004733654],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08757168,0.0003766783,0.8986333,0.0002358578,0.0001219265,0.00003956771,0.00009055085,0.00144388,0.01148652],"genre_scores_gemma":[0.8518888,0.0006045876,0.1425775,0.00008400983,0.00002951245,0.00008023195,0.000202019,0.0002332345,0.004300077],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002497768,"threshold_uncertainty_score":0.008355856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01157604403431168,"score_gpt":0.2383938593851884,"score_spread":0.2268178153508767,"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."}}