{"id":"W4414891569","doi":"10.1016/j.epsr.2025.112203","title":"A computationally efficient approach for power semiconductor loss estimation of modular multilevel converters in EMT simulations","year":2025,"lang":"en","type":"article","venue":"Electric Power Systems Research","topic":"HVDC Systems and Fault Protection","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Manitoba Hydro; University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Modular design; Converters; Transient (computer programming); Power (physics); Steady state (chemistry); Component (thermodynamics); Semiconductor device; Control theory (sociology)","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":[0.001214251,0.0001471486,0.0003069262,0.001110401,0.0001016413,0.00005504058,0.0001817916,0.0001647256,0.000004651712],"category_scores_gemma":[0.0002297719,0.000149884,0.00006294352,0.001362815,0.00003330869,0.00009045903,0.00002235331,0.0002890537,0.000005219545],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004607555,"about_ca_system_score_gemma":0.00014492,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001784949,"about_ca_topic_score_gemma":0.000002800804,"domain_scores_codex":[0.9980479,0.0001839249,0.0005807191,0.000287516,0.0004770092,0.000422964],"domain_scores_gemma":[0.9988312,0.0003850864,0.00005578732,0.0002401784,0.0004337296,0.00005398652],"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":[0.00002700091,0.00009134255,0.0001073405,0.0005328291,0.00005810594,8.696852e-7,0.0005856176,0.9697898,0.02696795,0.001013396,0.0003283327,0.0004973792],"study_design_scores_gemma":[0.0008211488,0.00006294976,0.001316963,0.0001393599,0.000004081816,0.000003703181,0.0001613428,0.995181,0.001893679,0.00005289309,0.0002413124,0.0001216146],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3510644,0.0005692186,0.6455426,0.00001112018,0.0002864414,0.001902165,0.00002976521,0.00006682563,0.0005275469],"genre_scores_gemma":[0.9985241,0.000002388502,0.0007793654,0.000002701079,0.00001671113,0.0003864872,0.00003588333,0.00002650484,0.0002258971],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6474597,"threshold_uncertainty_score":0.6112093,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02707666248400148,"score_gpt":0.3231832898970756,"score_spread":0.2961066274130741,"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."}}