{"id":"W2499176279","doi":"10.1109/pedg.2016.7527097","title":"An optimization approach for designing multilevel converters","year":2016,"lang":"en","type":"article","venue":"","topic":"Multilevel Inverters and Converters","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Converters; Inductance; Topology (electrical circuits); Rectifier (neural networks); Network topology; Electronic engineering; Power (physics); Power electronics; Inverter; Computer science; Diode; Semiconductor device; Capacitor; Key (lock); Topology optimization; Engineering; Electrical engineering; Voltage; Materials science; Finite element method; Physics","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":[0.00008121858,0.0001489811,0.0001307966,0.00006377859,0.00004771178,0.00003163095,0.0001481425,0.00007590889,0.0001390484],"category_scores_gemma":[0.000007239124,0.0001041677,0.00005157738,0.00003699193,0.00002631108,0.000332315,0.00000645554,0.00002766969,0.000008204951],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004838967,"about_ca_system_score_gemma":0.000008301806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006229978,"about_ca_topic_score_gemma":5.698808e-7,"domain_scores_codex":[0.9992909,0.00001182877,0.0001617655,0.0002027109,0.00007777532,0.0002549888],"domain_scores_gemma":[0.9995961,0.00004583035,0.00001671788,0.0001958707,0.00003883294,0.0001066711],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003576812,0.00005416843,0.0004168982,0.00008499591,0.00008637764,7.735256e-7,0.0004691784,0.3122494,0.06201362,0.0004322907,0.003874857,0.6202816],"study_design_scores_gemma":[0.0008592267,0.00002831906,0.00005760168,0.00001083969,0.00001000724,0.00000143821,0.00009353465,0.9859455,0.01263554,0.00001597206,0.0001241023,0.0002179871],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0005641966,0.000008613883,0.9970869,0.00002064663,0.0001959933,0.0002894197,0.00001277435,0.0004602878,0.001361144],"genre_scores_gemma":[0.6791148,0.000007749803,0.3203156,0.0001428853,0.00004281081,0.00008741004,0.00001613174,0.00003889936,0.0002337664],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6785505,"threshold_uncertainty_score":0.4247836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02206689268450836,"score_gpt":0.2200884655639414,"score_spread":0.1980215728794331,"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."}}