{"id":"W1528147424","doi":"10.1109/mwsym.2015.7167056","title":"Design of a chebyshev microstrip filter using the reflected group delay method and the aggressive space mapping technique","year":2015,"lang":"en","type":"article","venue":"","topic":"Microwave Engineering and Waveguides","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Chebyshev filter; Space mapping; Filter (signal processing); Microstrip; Group delay and phase delay; Computer science; Filter design; Group (periodic table); Electronic engineering; Algorithm; Engineering; Physics; Computer vision","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":[0.000330669,0.0005135581,0.0003969258,0.0002825861,0.0003147058,0.0004900923,0.0006750324,0.0007484045,0.0017449],"category_scores_gemma":[0.0003342796,0.0002743843,0.0005170122,0.0003268927,0.00027603,0.0004781598,0.0001550329,0.0003274082,0.0006659333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007320079,"about_ca_system_score_gemma":0.000843555,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00139865,"about_ca_topic_score_gemma":0.002324594,"domain_scores_codex":[0.9998136,0.0000308552,0.000008658883,0.00004016344,0.00008043225,0.00002621053],"domain_scores_gemma":[0.999828,0.00004434074,0.00003757931,0.00001991421,0.00006105824,0.000009217598],"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":[0.0002033224,0.00009263603,0.0008802902,0.0001821192,0.000134361,0.0001904286,0.0001308919,0.05800029,0.8176631,0.02473827,0.0008934002,0.09689092],"study_design_scores_gemma":[0.0001288653,0.001102202,0.002131273,0.0000239617,0.0001252647,0.0008669889,0.00005079415,0.6154323,0.358603,0.002778221,0.01868861,0.00006850639],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03618162,0.0000929832,0.9601656,0.00006162935,0.00002662964,0.00007081246,0.00003680049,0.0004737874,0.002889998],"genre_scores_gemma":[0.2799892,0.0001480073,0.716082,0.00004762116,0.00003007694,0.0001474168,0.00007527784,0.00004798353,0.003432424],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0017449,"threshold_uncertainty_score":0.005837262,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04116230446288752,"score_gpt":0.2640571087385649,"score_spread":0.2228948042756774,"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."}}