{"id":"W2904500680","doi":"10.1002/pssa.201800505","title":"Large Periphery GaN HEMTs Modeling Using Distributed Gate Resistance","year":2018,"lang":"en","type":"article","venue":"physica status solidi (a)","topic":"GaN-based semiconductor devices and materials","field":"Physics and Astronomy","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut interdisciplinaire d'innovation technologique; Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Transistor; Optoelectronics; Materials science; Substrate (aquarium); High-electron-mobility transistor; Sheet resistance; Metal gate; Electrical resistance and conductance; Electrical engineering; Gate oxide; Nanotechnology; Engineering; Layer (electronics); Voltage","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":[0.00009477706,0.0005934131,0.000237638,0.0002431209,0.0000982968,0.0003566854,0.0008267444,0.0003563601,0.0007461868],"category_scores_gemma":[0.000215927,0.0001583809,0.0004709523,0.0001687349,0.0001629592,0.0005700461,0.000203433,0.0002594483,0.0003706028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003532508,"about_ca_system_score_gemma":0.0001648718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008959566,"about_ca_topic_score_gemma":0.00121702,"domain_scores_codex":[0.9998932,0.00001518649,0.000003467909,0.00003654136,0.00004187801,0.000009818254],"domain_scores_gemma":[0.9999206,0.00002410675,0.00001086436,0.00002327144,0.00001782647,0.000003324579],"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":[0.00006328464,0.00004821683,0.001521942,0.0001255078,0.00007044403,0.0004141979,0.0001188171,0.5872913,0.3660632,0.01702887,0.0006625391,0.02659167],"study_design_scores_gemma":[0.000003462818,0.00002931657,0.0006144312,0.000003485577,0.00001140589,0.0001117081,0.000007367336,0.9805297,0.01570949,0.001695663,0.001277966,0.000006024249],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1353362,0.0003645691,0.8530183,0.0000588328,0.00002846499,0.00003548561,0.000259076,0.0009331375,0.009965999],"genre_scores_gemma":[0.9518954,0.0002688681,0.04391765,0.00001622884,0.00001903856,0.00004776134,0.0001769975,0.0001009185,0.003557103],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0008959566,"threshold_uncertainty_score":0.002563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02646365536479452,"score_gpt":0.285746656615703,"score_spread":0.2592830012509085,"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."}}