{"id":"W3126419072","doi":"10.1109/apmc47863.2020.9331616","title":"Design of Ku-Band Multiplexer with High Power Dielectric Resonator Filters Using Neural Networks","year":2020,"lang":"en","type":"article","venue":"","topic":"Microwave Engineering and Waveguides","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Honeywell (Canada); Ontario Tech University","funders":"","keywords":"Multiplexer; Reflection coefficient; Electronic engineering; Ku band; Dielectric resonator; Diplexer; Resonator; Computer science; Scattering parameters; Filter (signal processing); Dielectric resonator antenna; Multiplexing; Materials science; Optics; Engineering; Telecommunications; Physics; Optoelectronics","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":[0.0002577832,0.0005632921,0.0003791944,0.0002032742,0.0002744609,0.0004108726,0.0007816408,0.0005906507,0.001189307],"category_scores_gemma":[0.000294327,0.00029933,0.0004858581,0.0001459726,0.0002449399,0.0006082623,0.0002051743,0.0003740271,0.0002897313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006819483,"about_ca_system_score_gemma":0.0003422654,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002576589,"about_ca_topic_score_gemma":0.004196126,"domain_scores_codex":[0.9998492,0.00002790523,0.000006711807,0.00004707793,0.00004666246,0.00002247215],"domain_scores_gemma":[0.9998934,0.00003075636,0.00003385201,0.000008472934,0.0000260604,0.000007415259],"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":[0.000223434,0.0001450718,0.00104092,0.0001351286,0.0001640397,0.0001863027,0.0001010133,0.7541408,0.1332559,0.007943651,0.0009043476,0.1017596],"study_design_scores_gemma":[0.000005927149,0.00005157054,0.0001115331,0.00000247205,0.00001532914,0.00002331597,0.00000406066,0.9903807,0.008639167,0.0002326119,0.0005277414,0.000005495069],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05205546,0.0001935141,0.9442206,0.00009409089,0.00002492618,0.00003015936,0.0000222004,0.0004412111,0.00291782],"genre_scores_gemma":[0.8090587,0.0002428341,0.1862033,0.00008305085,0.00002479394,0.000107541,0.00004897916,0.00004336149,0.004187413],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002576589,"threshold_uncertainty_score":0.005123198,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01564343743401601,"score_gpt":0.1854799573918045,"score_spread":0.1698365199577885,"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."}}