{"id":"W2136102193","doi":"10.1109/icmmt.2008.4540326","title":"Neural network based power amplifier dynamic modeling for wireless communications","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Power Amplifier Design","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Rimouski","funders":"","keywords":"Computer science; Digital signal processing; Amplifier; Field-programmable gate array; MATLAB; Electronic engineering; Code division multiple access; Behavioral modeling; Wireless; Code generation; Artificial neural network; Embedded system; Computer hardware; Key (lock); Engineering; Telecommunications; Bandwidth (computing)","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":[0.0001263302,0.0003869403,0.0002064105,0.0001716077,0.0001559355,0.0003602896,0.000508018,0.0005234787,0.002763164],"category_scores_gemma":[0.0004196227,0.0001793646,0.000328361,0.0001895317,0.0001772099,0.0006786748,0.0001610498,0.0005557519,0.0006480746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003568768,"about_ca_system_score_gemma":0.0002380843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003427256,"about_ca_topic_score_gemma":0.002817556,"domain_scores_codex":[0.9999045,0.00002185341,0.000004412933,0.00002174547,0.00003881954,0.000008577241],"domain_scores_gemma":[0.9999219,0.00003468609,0.000008059719,0.000007212005,0.00002594692,0.000002056033],"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":[0.00002397638,0.00001931395,0.0003104413,0.00006288127,0.00002464204,0.00006173795,0.00003307763,0.9464884,0.01043941,0.006934311,0.0006097397,0.034992],"study_design_scores_gemma":[8.322639e-7,0.000006144475,0.00006888113,0.000002447196,0.000003078712,0.00001188689,0.000001722606,0.9974616,0.0008646171,0.0007577933,0.0008192856,0.000001703311],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01226199,0.0003828651,0.9798632,0.000114256,0.00004520713,0.0000187205,0.00005276254,0.0004629797,0.006797927],"genre_scores_gemma":[0.8740199,0.00132372,0.09678689,0.0001232729,0.00006873835,0.000190569,0.000221283,0.0001405462,0.02712508],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003427256,"threshold_uncertainty_score":0.009243667,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03855879073442161,"score_gpt":0.2640623864181363,"score_spread":0.2255035956837147,"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."}}