{"id":"W2166659270","doi":"10.23919/eumc.2009.5296241","title":"Extended Hammerstein model for RF power amplifier behavior modeling","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Power Amplifier Design","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Amplifier; Wideband; Large-signal model; SIGNAL (programming language); Electronic engineering; Computer science; Filter (signal processing); Nonlinear system; RF power amplifier; Power (physics); Behavioral modeling; Control theory (sociology); Engineering; Bandwidth (computing); Telecommunications; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009785913,0.0002600324,0.0002324545,0.0001030516,0.00006878368,0.00004067696,0.0001964239,0.0001243243,0.00007545988],"category_scores_gemma":[0.00001301498,0.0002649771,0.0001252123,0.0001063562,0.0000125708,0.00028135,0.00001230486,0.0001486498,0.00003557593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000845999,"about_ca_system_score_gemma":0.00001715286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001687632,"about_ca_topic_score_gemma":0.000002151982,"domain_scores_codex":[0.9987246,0.000004507686,0.000303983,0.0003005468,0.0001581376,0.0005081847],"domain_scores_gemma":[0.9993364,0.00002631604,0.00001836171,0.0004078103,0.00006776905,0.0001433253],"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":[0.00001906283,0.00004377428,0.00000241265,0.000007757268,0.00001391833,0.00000260415,0.0002062125,0.9686748,0.01763684,0.004968312,0.001703614,0.006720696],"study_design_scores_gemma":[0.0004358774,0.00004635715,0.00001495032,0.000008326449,0.00002836974,0.00000451635,0.0000519609,0.9866112,0.002638279,0.009424788,0.0003729166,0.0003624388],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00885847,0.0001515978,0.9812078,0.00005057107,0.0002019,0.0005636214,0.00001634451,0.0007676709,0.008181988],"genre_scores_gemma":[0.8736205,0.000009570795,0.1238659,0.0002601353,0.00003926188,0.0001083162,0.00001226786,0.00006581906,0.002018285],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8647619,"threshold_uncertainty_score":0.9999803,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03361170956374996,"score_gpt":0.2723120971495712,"score_spread":0.2387003875858212,"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."}}