{"id":"W2123728811","doi":"10.1109/ccece.2011.6030535","title":"Evaluation of a digital predistion on FPGA for power amplifier linearization","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Power Amplifier Design","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Predistortion; Linearizer; Amplifier; Field-programmable gate array; Linearization; Computer science; Electronic engineering; Orthogonal frequency-division multiplexing; Linear amplifier; RF power amplifier; Electrical engineering; Engineering; Embedded system; Telecommunications; Nonlinear system; CMOS; 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":[],"consensus_categories":[],"category_scores_codex":[0.0002385671,0.00008752189,0.0000826806,0.00006603572,0.00001473616,0.00001074319,0.0000536329,0.00005508286,0.0001830463],"category_scores_gemma":[0.0001491647,0.00008444198,0.00003571753,0.00008452843,0.00001359036,0.0002258872,0.000005223736,0.00003562845,0.00002352533],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005597321,"about_ca_system_score_gemma":0.00001547815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":8.09929e-7,"about_ca_topic_score_gemma":7.641041e-7,"domain_scores_codex":[0.9993415,0.00001029135,0.000175602,0.0001129437,0.0002530502,0.0001065668],"domain_scores_gemma":[0.9994845,0.00003895669,0.00003181381,0.0001601484,0.0002554024,0.00002922787],"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":[0.0007322814,0.0009703579,0.001666625,0.0003504476,0.0006207853,0.000001148473,0.007604977,0.4643016,0.03141049,0.07728568,0.01450087,0.4005548],"study_design_scores_gemma":[0.002871542,0.0008886597,0.007498418,0.00008509246,0.0002630528,0.000003234758,0.0002199633,0.6987071,0.2052049,0.07981418,0.003729956,0.0007138379],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01095316,0.00001809197,0.9267257,0.000002908931,0.0002597079,0.0004962318,0.00003172495,0.0001564644,0.06135597],"genre_scores_gemma":[0.9937563,0.000001153225,0.005865411,0.000007117743,0.00002791558,0.00006808789,0.000045247,0.00002637251,0.0002024022],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9828031,"threshold_uncertainty_score":0.3443444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08084936915821561,"score_gpt":0.2758588380358097,"score_spread":0.1950094688775941,"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."}}