{"id":"W2971481554","doi":"10.1109/mwsym.2019.8700772","title":"Reduced-Cost Gradient-Based Optimization of Compact Microwave Components through Adaptive Broyden Updates","year":2019,"lang":"en","type":"article","venue":"","topic":"Microwave Engineering and Waveguides","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Speedup; Jacobian matrix and determinant; Benchmark (surveying); Convergence (economics); Computer science; Algorithm; Electrical impedance; Microwave; Mathematical optimization; Mathematics; Applied mathematics; Parallel computing; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007298368,0.0009031254,0.0008419228,0.0003798154,0.000208962,0.0006562656,0.000955854,0.0007472563,0.002129823],"category_scores_gemma":[0.0017758,0.0005452411,0.0003584977,0.0003633796,0.0005664639,0.0007019265,0.0005826623,0.0007924938,0.0006041008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005766645,"about_ca_system_score_gemma":0.0007739334,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002658055,"about_ca_topic_score_gemma":0.00352541,"domain_scores_codex":[0.9997744,0.00007511795,0.000007233725,0.00003138503,0.0000908066,0.00002103967],"domain_scores_gemma":[0.9996164,0.0002255385,0.00004043786,0.00003687271,0.00006581991,0.00001499381],"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":[0.00007026295,0.00003264908,0.0001552742,0.00006203871,0.00002094365,0.00003508726,0.00003530032,0.957449,0.003709198,0.007562888,0.0007094294,0.03015799],"study_design_scores_gemma":[0.000004374935,0.0000127635,0.00001489818,0.000001402274,0.000001041039,0.000003315628,0.000001587188,0.9990008,0.0003620241,0.0003872999,0.0002092257,0.000001158617],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01328872,0.0001299537,0.9841385,0.00007435201,0.00001951202,0.00003345681,0.00001712487,0.0003508992,0.001947404],"genre_scores_gemma":[0.4223567,0.0001668117,0.5707649,0.00009777368,0.00003255465,0.0002620325,0.0001183204,0.0003428356,0.005858127],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002658055,"threshold_uncertainty_score":0.00712496,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01733575096583343,"score_gpt":0.2144359738786826,"score_spread":0.1971002229128492,"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."}}