{"id":"W2120739110","doi":"10.1109/tpel.2006.890002","title":"Design and Comparison of High Performance Stationary-Frame Controllers for DVR Implementation","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Power Electronics","topic":"Power Quality and Harmonics","field":"Engineering","cited_by":153,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Control theory (sociology); Robustness (evolution); Weighting; Stationary Reference Frame; Voltage; Transient response; Computer science; Transient (computer programming); Control engineering; Frame (networking); Engineering; Control (management)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003713311,0.0001336672,0.0002012196,0.0001220395,0.0001067577,0.00001364845,0.0000670653,0.00008078213,0.00003589518],"category_scores_gemma":[0.000001415819,0.0001507403,0.00004410142,0.0001255849,0.00003179608,0.0001416091,3.058563e-7,0.000192965,0.000002688728],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001320939,"about_ca_system_score_gemma":0.00004962065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005942576,"about_ca_topic_score_gemma":0.00004405348,"domain_scores_codex":[0.9990288,0.00001902223,0.0003519009,0.000130284,0.0001448372,0.0003251651],"domain_scores_gemma":[0.9994684,0.0002482166,0.00005642968,0.0001135998,0.00006078318,0.00005261222],"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":[0.001063062,0.000283943,0.00003771194,0.0001805001,0.0004058751,4.768533e-7,0.003662312,0.8865186,0.02905937,0.003239461,0.0005974714,0.07495123],"study_design_scores_gemma":[0.003672484,0.001760138,0.0004856501,0.00002279044,0.0001312554,0.000004384036,0.000656791,0.2592769,0.7288449,0.0009554261,0.003786987,0.0004022479],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2736014,0.0002759127,0.7254305,0.00004027977,0.0001797214,0.0003469542,0.00003106306,0.00006656606,0.00002758698],"genre_scores_gemma":[0.9936984,0.0002693298,0.005882609,0.00004479397,0.000005335399,0.0000366593,0.0000113365,0.00002619395,0.00002535962],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7200971,"threshold_uncertainty_score":0.6147012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02192362751783691,"score_gpt":0.2960354938975882,"score_spread":0.2741118663797513,"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."}}