{"id":"W2971934423","doi":"10.1109/mwsym.2019.8701083","title":"Iterative Synthesis of Equi-Ripple Dual-band Filtering Functions With One Additional Transmission Zero","year":2019,"lang":"en","type":"article","venue":"","topic":"Microwave Engineering and Waveguides","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Passband; Ripple; Return loss; Dual (grammatical number); Prototype filter; Network synthesis filters; Band-pass filter; Filter (signal processing); Computer science; Control theory (sociology); Iterative method; Transmission (telecommunications); Topology (electrical circuits); Zero (linguistics); Position (finance); Multi-band device; Algorithm; Electronic engineering; Mathematics; Filter design; Telecommunications; Engineering; Artificial intelligence; Electrical engineering","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":[0.0005021857,0.0007446468,0.0003848952,0.0006321743,0.0002876831,0.0005583612,0.0005914915,0.0004207312,0.001521325],"category_scores_gemma":[0.0006431037,0.0003322347,0.0006518386,0.0003430329,0.0004137746,0.0005180844,0.0003762399,0.0004276622,0.0005035153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004282778,"about_ca_system_score_gemma":0.0003850433,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003696004,"about_ca_topic_score_gemma":0.0005521862,"domain_scores_codex":[0.9997227,0.00003615793,0.0000219885,0.00005035211,0.0001213852,0.00004734828],"domain_scores_gemma":[0.9996527,0.000104586,0.000069467,0.00006017317,0.00009769502,0.0000152822],"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":[0.0004308215,0.0001436461,0.0008295933,0.0003659393,0.00008729144,0.0003277445,0.0004234927,0.04889575,0.6812142,0.03908795,0.000812566,0.2273811],"study_design_scores_gemma":[0.00006647626,0.0005273755,0.0006711407,0.00004847662,0.00009913203,0.0006625339,0.0000679341,0.3553596,0.6269418,0.005125631,0.01036661,0.00006342689],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06390242,0.0001195209,0.9281079,0.00003639322,0.00003137394,0.00004966367,0.00002805452,0.0003744039,0.007350193],"genre_scores_gemma":[0.3942052,0.0001611395,0.6018148,0.00004986945,0.00002159072,0.0001101842,0.00009126134,0.0001180677,0.003427899],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001521325,"threshold_uncertainty_score":0.005089343,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007451077968533782,"score_gpt":0.1746788933380799,"score_spread":0.1672278153695461,"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."}}