{"id":"W1493090307","doi":"10.1109/mwscas.2003.1562539","title":"A large-signal neural network model for the dual gate MESFET","year":2006,"lang":"en","type":"article","venue":"","topic":"GaN-based semiconductor devices and materials","field":"Physics and Astronomy","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nortel (Canada); University of Ottawa","funders":"","keywords":"MESFET; Artificial neural network; Computer science; SIGNAL (programming language); Channel (broadcasting); Perceptron; Electronic engineering; Dual (grammatical number); Multilayer perceptron; Artificial intelligence; Engineering; Electrical engineering; Transistor; Voltage; Field-effect transistor; Telecommunications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002747725,0.0004350763,0.0003693411,0.0001916433,0.00022397,0.0005394703,0.0009759733,0.001077716,0.001788016],"category_scores_gemma":[0.0006184955,0.0002685507,0.0003827605,0.0002708655,0.0003750694,0.0007874134,0.0002858148,0.0007639072,0.000353831],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007209816,"about_ca_system_score_gemma":0.000525167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004948319,"about_ca_topic_score_gemma":0.005302084,"domain_scores_codex":[0.9998798,0.00002354336,0.000005917052,0.00003762214,0.00003757714,0.00001544728],"domain_scores_gemma":[0.9998578,0.0000695248,0.00001740676,0.000009397088,0.00003874172,0.000007164353],"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":[0.00003301283,0.00001394848,0.0001661562,0.00002998432,0.00001273431,0.00004771612,0.00001414874,0.9873613,0.003569243,0.003001733,0.0003095068,0.005440504],"study_design_scores_gemma":[0.000001138102,0.000005025547,0.0000432845,0.00000109695,0.000001583142,0.00000508811,8.404309e-7,0.9991556,0.0002553248,0.0004369262,0.00009218865,0.000001848711],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07381702,0.0006783808,0.9131361,0.0007431467,0.0001263354,0.00005699933,0.0004216648,0.0006499736,0.01037025],"genre_scores_gemma":[0.9340133,0.0003702678,0.05058616,0.0001439651,0.00005428844,0.0001703231,0.0002369474,0.0000544539,0.01437027],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004948319,"threshold_uncertainty_score":0.009839058,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01843484862625951,"score_gpt":0.243613269560238,"score_spread":0.2251784209339786,"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."}}