{"id":"W2344968456","doi":"10.1109/tec.2015.2503735","title":"Multirate EMTP-Type Induction Machine Models","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Energy Conversion","topic":"HVDC Systems and Fault Protection","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Emtp; Interfacing; Reactance; Computer science; Electric power system; Power (physics); Control engineering; Focus (optics); Voltage; Engineering; Electronic engineering; Control theory (sociology); Electrical engineering; Artificial intelligence","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":[0.00007410882,0.0001726221,0.0001349049,0.000149093,0.0001332919,0.00001480044,0.00007434869,0.0001702405,0.0001738374],"category_scores_gemma":[9.909907e-7,0.0001323023,0.00007534043,0.000220371,0.00002364183,0.0003910596,6.131066e-7,0.0001209082,0.0001429497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001654767,"about_ca_system_score_gemma":0.00001123775,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002550311,"about_ca_topic_score_gemma":0.00004930732,"domain_scores_codex":[0.9992061,0.00003761925,0.0001908273,0.0002112613,0.0001584385,0.0001957567],"domain_scores_gemma":[0.9995853,0.00002490945,0.00002818623,0.0002193031,0.00005625839,0.00008602058],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001274656,0.00006822303,0.000003131515,0.00003545828,0.0000867851,0.000005169961,0.0001127601,0.4018256,0.3618419,0.0001609598,0.0005113376,0.2352211],"study_design_scores_gemma":[0.001160921,0.0001763728,0.00001457301,0.0001052338,0.0000274227,0.00002014469,0.00003465387,0.3712668,0.6108423,0.0001419439,0.01586197,0.0003477127],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0488786,0.00006416074,0.9465125,0.0000685959,0.003101236,0.00009165173,0.00001390761,0.000528311,0.000741088],"genre_scores_gemma":[0.9974768,0.0004327383,0.0001490482,0.0000297914,0.00008328076,0.00002509529,0.000002515973,0.00003998936,0.001760804],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9485981,"threshold_uncertainty_score":0.5395132,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01569108086965389,"score_gpt":0.1965928947148639,"score_spread":0.18090181384521,"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."}}