{"id":"W2885930879","doi":"10.1109/mwsym.2018.8439836","title":"Rapid Design Tuning of Miniaturized Rat-Race Couplers Using Regression-Based Equivalent Network Surrogates","year":2018,"lang":"en","type":"article","venue":"","topic":"Microwave Engineering and Waveguides","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Rat-race coupler; Representation (politics); Nonlinear system; Computer science; Equivalent circuit; Electronic engineering; Hybrid coupler; Topology (electrical circuits); Algorithm; Control theory (sociology); Physics; Engineering; Telecommunications; Electrical engineering; Power dividers and directional couplers; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.0004936786,0.0002552101,0.0003364157,0.0001103283,0.00008467698,0.00002692092,0.0001759666,0.000116143,0.0002836194],"category_scores_gemma":[0.00007374604,0.0002221152,0.00009529365,0.0003103214,0.00008781499,0.00007140682,0.00002849808,0.0001320471,0.00001398286],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005851521,"about_ca_system_score_gemma":0.00004517236,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001208437,"about_ca_topic_score_gemma":0.000002242481,"domain_scores_codex":[0.9987578,0.00004995941,0.0003721293,0.0002009098,0.0001776191,0.0004415983],"domain_scores_gemma":[0.9990962,0.0003065123,0.00006522278,0.00032288,0.0001011243,0.0001080801],"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":[0.00003566566,0.00001126096,0.00008977272,0.00009147266,0.00005438674,0.000003182106,0.0001122346,0.5811911,0.4103745,0.00003163022,0.007484803,0.0005199939],"study_design_scores_gemma":[0.0003886909,0.00005067344,0.00003708544,0.0002983438,0.00002280858,0.00000272415,0.00002971041,0.7220484,0.2756489,0.00001629197,0.001247152,0.0002092087],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3348545,0.001878381,0.6600536,0.00002877065,0.001306527,0.000245275,0.000004016033,0.0006110459,0.001017952],"genre_scores_gemma":[0.8144664,0.0000522908,0.1849857,0.00002176962,0.0002749159,0.000003801089,0.000005882627,0.00006075318,0.0001285093],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.479612,"threshold_uncertainty_score":0.9057595,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03846449267149318,"score_gpt":0.2474537366024994,"score_spread":0.2089892439310062,"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."}}