{"id":"W1480660824","doi":"","title":"Efficient design optimization of microwave circuits using parallel computational methods","year":2012,"lang":"en","type":"article","venue":"European Microwave Integrated Circuit Conference","topic":"Microwave Engineering and Waveguides","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Speedup; Computer science; Mathematical optimization; Computation; Electronic circuit; Space mapping; Filter (signal processing); Point (geometry); Microwave; Optimization problem; Algorithm; Parallel computing; Mathematics; Engineering; Telecommunications","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":[0.001241331,0.0004765392,0.0004621507,0.0003187938,0.00009548344,0.00008030362,0.0003849856,0.0001264456,0.0001416056],"category_scores_gemma":[0.0001450093,0.0004959957,0.0001425959,0.0005241946,0.0001485455,0.0001449522,0.00005195301,0.0004117544,0.00007989644],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001794749,"about_ca_system_score_gemma":0.00009715268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001004899,"about_ca_topic_score_gemma":3.346705e-7,"domain_scores_codex":[0.9974041,0.0005558181,0.0007987476,0.0003503186,0.0002206665,0.0006703472],"domain_scores_gemma":[0.9985914,0.0002048214,0.000175261,0.0003744299,0.0004210532,0.0002330912],"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":[0.000003269688,0.00004271327,0.00002455428,0.00005155723,0.00007924197,0.000004117001,0.000724055,0.6415482,0.3498503,0.0008625664,0.0001134932,0.00669594],"study_design_scores_gemma":[0.0004070758,0.00003117053,0.0002339324,0.0002314353,0.00006942132,0.0001045129,0.000171207,0.9164766,0.08132275,0.0001074612,0.0002899431,0.0005544686],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0169318,0.001214556,0.9694206,0.000004383693,0.0005761821,0.0002944415,0.00003196471,0.0003566398,0.01116946],"genre_scores_gemma":[0.7072412,0.00003162037,0.2924174,0.00002166681,0.00008157722,0.000003731512,0.0000572993,0.0001041192,0.00004133825],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6903095,"threshold_uncertainty_score":0.9997492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06158739669481186,"score_gpt":0.2677910548631532,"score_spread":0.2062036581683413,"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."}}