{"id":"W2125132813","doi":"10.1109/mwsym.2003.1212521","title":"Novel adaptive predistortion technique for cross coupled filters","year":2003,"lang":"en","type":"article","venue":"","topic":"Microwave Engineering and Waveguides","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"COM DEV International","funders":"","keywords":"Predistortion; Electronic engineering; Computer science; Multiplexer; Adaptive filter; Equalization (audio); Adaptive equalizer; Filter (signal processing); Communications satellite; Insertion loss; Telecommunications; Engineering; Satellite; Electrical engineering; Multiplexing; Amplifier; 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":[0.0001708641,0.0004169752,0.0001732275,0.0003686112,0.0002709089,0.0002814061,0.0005423943,0.0004056896,0.002142079],"category_scores_gemma":[0.0004107154,0.00022406,0.0002289411,0.0002438512,0.0002427683,0.0004543688,0.0002774952,0.0006312705,0.0006027797],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002744178,"about_ca_system_score_gemma":0.0002212039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003454264,"about_ca_topic_score_gemma":0.0008803349,"domain_scores_codex":[0.9998199,0.00002320162,0.000008441125,0.0000387342,0.00009286562,0.00001679205],"domain_scores_gemma":[0.9998161,0.00006043066,0.00002740232,0.00002656547,0.0000592694,0.0000103006],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001628471,0.00003663342,0.0002927396,0.0001377157,0.00005671137,0.0003377226,0.0001500232,0.009641034,0.7958342,0.005708504,0.001200183,0.1864415],"study_design_scores_gemma":[0.00003338419,0.0003277933,0.001410083,0.00002394454,0.00008161273,0.002180891,0.00003380639,0.1691008,0.7902058,0.001664045,0.03486706,0.00007092834],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04525096,0.0008381982,0.9482334,0.0001407492,0.0001632134,0.00005185212,0.00003309761,0.001299436,0.003989053],"genre_scores_gemma":[0.4149586,0.000957061,0.5712642,0.000201187,0.0001934037,0.00006784355,0.00009305104,0.0001319409,0.01213277],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002142079,"threshold_uncertainty_score":0.007165968,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01534478276652382,"score_gpt":0.2269572715626331,"score_spread":0.2116124887961093,"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."}}