{"id":"W2155892057","doi":"10.1002/mop.25660","title":"Empirical and deterministic approach for the optimization of wideband RF power amplifiers' behavior modeling and predistortion structure","year":2010,"lang":"en","type":"article","venue":"Microwave and Optical Technology Letters","topic":"Advanced Power Amplifier Design","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Predistortion; Wideband; Amplifier; Linearization; LDMOS; W-CDMA; Electronic engineering; Computer science; RF power amplifier; Engineering; Nonlinear system; Electrical engineering; Code division multiple access; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001084262,0.000668674,0.0005936674,0.0005543596,0.0002691646,0.0004980331,0.0006475281,0.0005362805,0.001749082],"category_scores_gemma":[0.003132868,0.0006951605,0.0005343273,0.0002580928,0.0005057407,0.0005798255,0.000406842,0.0007862932,0.0002291551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008278314,"about_ca_system_score_gemma":0.001242432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003411658,"about_ca_topic_score_gemma":0.004112385,"domain_scores_codex":[0.9996908,0.0001144346,0.00001089972,0.00004392948,0.0001105644,0.00002942935],"domain_scores_gemma":[0.998744,0.0008801443,0.0001227079,0.00007313031,0.000161281,0.00001872254],"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":[0.000007492275,0.00001002499,0.000107434,0.00001363158,0.00001077062,0.00000926207,0.000009407595,0.9901229,0.0007904323,0.003892441,0.00005719301,0.004969061],"study_design_scores_gemma":[0.000001903563,0.00000675466,0.00003599705,0.000001933835,0.000001801003,0.000002440348,0.000001384894,0.998849,0.0001969554,0.0007839841,0.0001163741,0.000001478061],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01550411,0.00008177055,0.9826009,0.0000706849,0.000005204584,0.00002161284,0.00002069393,0.000103893,0.001591157],"genre_scores_gemma":[0.6259513,0.0002499488,0.3699468,0.00006824287,0.0000275301,0.0002681536,0.00009600175,0.00009687158,0.003295166],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003411658,"threshold_uncertainty_score":0.006783605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01077644526565582,"score_gpt":0.2332951839849592,"score_spread":0.2225187387193034,"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."}}