{"id":"W2335353069","doi":"10.1109/tmtt.2014.2360387","title":"Baseband Equivalent Volterra Series for Behavioral Modeling and Digital Predistortion of Power Amplifiers Driven With Wideband Carrier Aggregated Signals","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Microwave Theory and Techniques","topic":"Advanced Power Amplifier Design","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Volterra series; Predistortion; Baseband; Wideband; Linearization; Amplifier; Control theory (sociology); Electronic engineering; Passband; Series (stratigraphy); Computer science; Behavioral modeling; Mathematics; Nonlinear system; Bandwidth (computing); Telecommunications; Engineering; Physics; Band-pass filter","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":[],"consensus_categories":[],"category_scores_codex":[0.0001743421,0.0002193178,0.000238306,0.0001266424,0.0001022709,0.00003995531,0.0000578672,0.000101388,0.000008662721],"category_scores_gemma":[0.000004231717,0.0002010037,0.00005251934,0.00006645718,0.0001824247,0.0003748781,0.000001399324,0.000130186,1.416821e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003134029,"about_ca_system_score_gemma":0.00001002842,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002321788,"about_ca_topic_score_gemma":0.000005693861,"domain_scores_codex":[0.9992419,0.00003725719,0.0002246673,0.0002262848,0.00008146195,0.0001883854],"domain_scores_gemma":[0.9995265,0.0001108409,0.00004656241,0.0001709452,0.0000684784,0.00007669062],"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":[0.001266402,0.00008410033,0.0000195708,0.0002234794,0.0001236822,0.000001882109,0.00124637,0.02455289,0.9441535,0.0006935105,0.00002754017,0.02760706],"study_design_scores_gemma":[0.0003963778,0.0008519521,0.00000107772,0.0002199485,0.0001076886,0.00002834712,0.0001770486,0.001772475,0.9905009,0.005518119,0.0001274951,0.0002985976],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2443596,0.00008417622,0.7546199,0.000003200174,0.000041027,0.0004260264,0.0001543497,0.0002166805,0.00009509705],"genre_scores_gemma":[0.9953264,0.00006221538,0.004307009,0.00001028991,0.000010422,0.0001482808,0.0000106807,0.00005154361,0.00007316775],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7509668,"threshold_uncertainty_score":0.8196694,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01131189547326154,"score_gpt":0.2310684402734054,"score_spread":0.2197565448001439,"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."}}