{"id":"W1906687465","doi":"10.18725/oparu-936","title":"Diplexer design using pre-synthesized waveguide filters with strongly dispersive inverters","year":2001,"lang":"en","type":"article","venue":"OPen Access Repositorium der Universität Ulm (OPARU) (Ulm University)","topic":"Microwave Engineering and Waveguides","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Diplexer; Passband; Attenuation; Waveguide filter; Resonator; Prototype filter; Filter (signal processing); Electronic engineering; Band-pass filter; Waveguide; Distributed element filter; Transmission (telecommunications); Network synthesis filters; Computer science; Optics; Physics; Filter design; Engineering; Telecommunications; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001750883,0.00069351,0.0006634206,0.0007783926,0.0006078386,0.0009175711,0.002802694,0.0002520339,0.0001447607],"category_scores_gemma":[0.00002248716,0.0007592276,0.0001871641,0.001496821,0.0001659976,0.006630849,0.0009122976,0.0004329789,0.00001999311],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001275746,"about_ca_system_score_gemma":0.0002337753,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001234007,"about_ca_topic_score_gemma":0.00009776547,"domain_scores_codex":[0.9972714,0.0001615132,0.0003494303,0.0008586422,0.0004407742,0.000918233],"domain_scores_gemma":[0.9980685,0.0001435951,0.0001840261,0.0008670866,0.0002287287,0.0005081031],"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":[0.001957042,0.0002158063,0.00550373,0.0001979832,0.002233661,0.006040841,0.001780265,0.9043971,0.06820993,0.001024341,0.00751014,0.0009291078],"study_design_scores_gemma":[0.01431889,0.0007517023,0.00554155,0.001691595,0.003731108,0.00139419,0.01076957,0.63577,0.1314957,0.00008832446,0.1867876,0.007659798],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2774225,0.0001882999,0.6515729,0.0001755602,0.001420893,0.001604907,0.00004687495,0.0008841761,0.0666839],"genre_scores_gemma":[0.9787965,0.0001468439,0.009082222,0.00003766712,0.0001945381,0.000002585909,0.00003474575,0.0001460851,0.01155881],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7013741,"threshold_uncertainty_score":0.9994859,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03583851815023759,"score_gpt":0.2533269496139993,"score_spread":0.2174884314637617,"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."}}