{"id":"W3010921435","doi":"10.1109/apmc46564.2019.9038761","title":"Bandwidth Performance Analysis of DLM PAs Including the Class-A/B/J Continuum","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced Power Amplifier Design","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Bandwidth (computing); Wideband; MATLAB; Amplifier; Computer science; Electronic engineering; Biasing; Control theory (sociology); Topology (electrical circuits); Physics; Voltage; Engineering; Electrical engineering; Telecommunications; Artificial intelligence","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":[0.0002717004,0.0005535687,0.0002559637,0.0007972973,0.0002575628,0.0004348365,0.0003890521,0.0004621267,0.001192386],"category_scores_gemma":[0.0007041365,0.0001889035,0.0004079659,0.0004214598,0.0003105631,0.0008423345,0.0003219248,0.0003925957,0.0005742421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003276611,"about_ca_system_score_gemma":0.0001390385,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005932333,"about_ca_topic_score_gemma":0.0006096236,"domain_scores_codex":[0.9996879,0.00003535004,0.00001285955,0.00006514404,0.0001726064,0.0000261466],"domain_scores_gemma":[0.9996835,0.0001313079,0.00006053367,0.00003433103,0.00008225963,0.000008122226],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003154594,0.00006726666,0.004703885,0.0004455129,0.00008660775,0.0004538588,0.0004665913,0.09299143,0.7265261,0.02303605,0.0009850923,0.1499222],"study_design_scores_gemma":[0.00001201456,0.0002107747,0.004660575,0.00005865934,0.00005794835,0.0006817337,0.0001189427,0.748186,0.2302309,0.006099644,0.009641012,0.00004174508],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2191946,0.00220964,0.7520629,0.0001686237,0.00005027886,0.00004653287,0.0001445135,0.0012715,0.02485145],"genre_scores_gemma":[0.9557771,0.0006435784,0.04118091,0.0000338329,0.00002321519,0.0000453574,0.00008258578,0.0001013721,0.00211205],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001192386,"threshold_uncertainty_score":0.003988922,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01725347421116926,"score_gpt":0.2245105436092786,"score_spread":0.2072570693981093,"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."}}