{"id":"W4399563346","doi":"10.1109/tia.2024.3413045","title":"A Comprehensive Analysis of GaN-HEMT-Based Class E Resonant Inverter Using Modified Resonant Gate Driver Circuit","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Industry Applications","topic":"GaN-based semiconductor devices and materials","field":"Physics and Astronomy","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"High-electron-mobility transistor; Inverter; Gate driver; Resonant inverter; RLC circuit; Optoelectronics; Electrical engineering; Gallium nitride; Logic gate; Materials science; Electronic engineering; Engineering; Capacitor; Transistor; Voltage; Nanotechnology","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00009233902,0.0002613149,0.0004168178,0.0005011616,0.0002219093,0.00008846707,0.0002187179,0.0002253767,0.001156799],"category_scores_gemma":[3.740017e-7,0.0002505318,0.000359296,0.001449855,0.0001290931,0.0001212741,0.000001982944,0.0005204188,0.00003735326],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007423548,"about_ca_system_score_gemma":0.0002234987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007300712,"about_ca_topic_score_gemma":0.00001869367,"domain_scores_codex":[0.9983968,0.00007318539,0.0005083993,0.0004991878,0.0002335849,0.0002889017],"domain_scores_gemma":[0.9988316,0.0001585761,0.0001411749,0.000578511,0.000152322,0.0001378256],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006145948,0.0008669214,0.0003812618,0.0002178485,0.003306927,0.000005453785,0.0006631751,0.286223,0.6819713,0.005876525,0.0005236537,0.01990258],"study_design_scores_gemma":[0.0009414418,0.00007999548,0.0007829323,0.0002906915,0.004825925,0.000002502446,0.0009736309,0.5685956,0.4044965,0.001077768,0.01709928,0.0008337412],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4430964,0.00004192818,0.5538405,0.0001517575,0.0001974329,0.0005077352,0.001670162,0.00008678033,0.0004073233],"genre_scores_gemma":[0.9988354,0.000003312568,0.0002054058,0.0001216335,0.00009874162,0.0003421934,0.0001056987,0.00003744293,0.0002502163],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5557389,"threshold_uncertainty_score":0.9999947,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05228654987700538,"score_gpt":0.295713189844252,"score_spread":0.2434266399672466,"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."}}