{"id":"W2305446766","doi":"10.1109/tpel.2015.2504489","title":"Fast Transient Response of Series Resonant Converters Using Average Geometric Control","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Power Electronics","topic":"Advanced DC-DC Converters","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Control theory (sociology); Overshoot (microwave communication); Converters; Controller (irrigation); Transient (computer programming); Transient response; Nonlinear system; Linear system; SIGNAL (programming language); Operating point; Small-signal model; Computer science; Power (physics); Engineering; Electronic engineering; Mathematics; Voltage; Physics; Control (management)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002750991,0.000327177,0.0002619952,0.0002498464,0.0001590129,0.0003354026,0.0003876754,0.0001913744,0.001036307],"category_scores_gemma":[0.0004984858,0.000088655,0.0002035977,0.0001476311,0.0002644599,0.0003006052,0.0002639435,0.0001978813,0.0001878671],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002829137,"about_ca_system_score_gemma":0.0001623482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005871279,"about_ca_topic_score_gemma":0.0004357919,"domain_scores_codex":[0.9998029,0.00003492675,0.00001143285,0.00003459835,0.0001006355,0.00001554611],"domain_scores_gemma":[0.9998349,0.00005452289,0.00003319835,0.00002478562,0.00004694737,0.000005613035],"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":[0.00060314,0.0001286979,0.001503787,0.0003087017,0.00005312556,0.000229184,0.0003711311,0.3961188,0.3766594,0.01122342,0.00131532,0.2114853],"study_design_scores_gemma":[0.00001990836,0.0003471491,0.000563581,0.000008579719,0.00001452321,0.00009271941,0.00002573303,0.9298959,0.06537664,0.001385951,0.002257064,0.00001217474],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2422369,0.0002256897,0.7399647,0.0001147401,0.0000527572,0.00006505866,0.00002979151,0.002047895,0.01526229],"genre_scores_gemma":[0.9871448,0.00004709482,0.01196618,0.00001282592,0.000004419183,0.00001485263,0.00001390488,0.00002015995,0.0007757411],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001036307,"threshold_uncertainty_score":0.003466845,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01068730258292583,"score_gpt":0.2178632126115789,"score_spread":0.2071759100286531,"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."}}