{"id":"W3202304473","doi":"10.3390/en14196098","title":"High Power Normally-OFF GaN/AlGaN HEMT with Regrown p Type GaN","year":2021,"lang":"en","type":"article","venue":"Energies","topic":"GaN-based semiconductor devices and materials","field":"Physics and Astronomy","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"CMC Microsystems (Canada); Institut interdisciplinaire d'innovation technologique; Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies; Fonds de recherche du Québec – Nature et technologies; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"High-electron-mobility transistor; Materials science; Doping; Optoelectronics; Wide-bandgap semiconductor; Transistor; Molecular beam epitaxy; Epitaxy; Layer (electronics); Electrical engineering; Nanotechnology; Voltage; Engineering","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":[0.0001309532,0.000234506,0.000284652,0.0001005547,0.0001336278,0.0003304311,0.0006018089,0.0002842105,0.001023841],"category_scores_gemma":[0.0001738207,0.0001230728,0.0002321003,0.0001456287,0.0001624981,0.0003173705,0.0001335439,0.0002713268,0.00038428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002406917,"about_ca_system_score_gemma":0.0001276948,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005356136,"about_ca_topic_score_gemma":0.0009420539,"domain_scores_codex":[0.9998858,0.00001042615,0.000005736504,0.00002903131,0.00004677676,0.00002228669],"domain_scores_gemma":[0.9998623,0.00003025743,0.00002579035,0.00002836619,0.00003671057,0.00001660117],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001261412,0.00002711283,0.0006342233,0.00005858203,0.00002134647,0.000327494,0.00004539037,0.0006011694,0.9947528,0.0002157014,0.0002620622,0.002927905],"study_design_scores_gemma":[0.0000526031,0.001159822,0.007646251,0.0000135858,0.00005609635,0.001232808,0.00005316002,0.01066434,0.9756249,0.0003107915,0.003168962,0.00001680743],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9927839,0.0002911229,0.004458253,0.00006849531,0.00004030312,0.00002092744,0.0002236976,0.0001824825,0.00193074],"genre_scores_gemma":[0.9943442,0.0001198758,0.003419181,0.00003741735,0.00001707226,0.00001295248,0.0001317977,0.0000355372,0.001882036],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001023841,"threshold_uncertainty_score":0.003425062,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006976787864982775,"score_gpt":0.2093276644810554,"score_spread":0.2023508766160727,"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."}}