{"id":"W2068856655","doi":"10.1109/icuwb.2015.7324481","title":"Multiple Model Linearization Solution for Cellular Base Station Power Amplifiers","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Power Amplifier Design","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Amplifier; Adjacent channel power ratio; Base station; Wideband; Linearization; Computer science; W-CDMA; Electronic engineering; Code division multiple access; Power (physics); Adjacent channel; RF power amplifier; Telecommunications; Engineering; Nonlinear system; Bandwidth (computing); 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":[0.0002561033,0.0006115714,0.0004806023,0.000207622,0.000325832,0.000631134,0.0005565905,0.0006610054,0.003146171],"category_scores_gemma":[0.0005534508,0.0003307926,0.0005053819,0.0002652551,0.0003068712,0.0004516226,0.0005880279,0.0008725804,0.0007140933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004607357,"about_ca_system_score_gemma":0.0005222579,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003709314,"about_ca_topic_score_gemma":0.003607567,"domain_scores_codex":[0.9998544,0.00003741031,0.000006211597,0.00003016974,0.00005652739,0.00001530591],"domain_scores_gemma":[0.9998652,0.00005136698,0.00001951578,0.00001045605,0.00004846346,0.000004963041],"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":[0.00005604035,0.00003124969,0.0004296699,0.0002241604,0.000049751,0.0001938359,0.0001997381,0.8811008,0.01348096,0.02134694,0.002124587,0.08076219],"study_design_scores_gemma":[0.000005386334,0.00002941925,0.00006006366,0.00000680688,0.000005864781,0.00003063445,0.00001734312,0.9960783,0.0009366386,0.00146739,0.001356777,0.000005341248],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004645176,0.0002034433,0.9917608,0.0001019977,0.00002613184,0.00002040837,0.00002050024,0.000185527,0.003036087],"genre_scores_gemma":[0.8097174,0.0008118664,0.168587,0.0001462904,0.00008670807,0.0001988651,0.0001383426,0.00008324174,0.02023034],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003709314,"threshold_uncertainty_score":0.01052499,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0447495690005504,"score_gpt":0.2459360326842922,"score_spread":0.2011864636837418,"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."}}