{"id":"W2132659334","doi":"10.2528/pierb12052406","title":"CSRRS FOR EFFICIENT REDUCTION OF THE ELECTROMAGNETIC INTERFERENCES AND MUTUAL COUPLING IN MICROSTRIP CIRCUITS","year":2012,"lang":"en","type":"article","venue":"Progress In Electromagnetics Research B","topic":"Antenna Design and Analysis","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Waterloo","keywords":"Reduction (mathematics); Coupling (piping); Electronic circuit; Microstrip; Computer science; Materials science; Electronic engineering; Electrical engineering; Engineering; Mathematics; Composite material","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001597085,0.0003621929,0.0002300663,0.0002221807,0.0000891308,0.0002848127,0.0004650876,0.0002856674,0.0008311385],"category_scores_gemma":[0.0003129453,0.0001515998,0.0002164551,0.0001730468,0.0002150687,0.0003658581,0.0002275108,0.0002136222,0.0003968959],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002042376,"about_ca_system_score_gemma":0.00008592532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001016975,"about_ca_topic_score_gemma":0.0002744353,"domain_scores_codex":[0.9997775,0.00004751753,0.0000109348,0.00002971632,0.0001102733,0.00002409916],"domain_scores_gemma":[0.9997739,0.0000660955,0.00008922242,0.00003054463,0.00003046092,0.000009721309],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006964442,0.00003940697,0.0002935055,0.0001045305,0.00002352703,0.0001163902,0.00005302322,0.004876934,0.9470116,0.005675518,0.0003318186,0.04140408],"study_design_scores_gemma":[0.0000410216,0.0007027462,0.001038813,0.00001496043,0.00004750984,0.0005726894,0.0000374446,0.1157572,0.8668991,0.001106483,0.01376009,0.00002192332],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4720915,0.00207214,0.5134619,0.0001625218,0.00008318474,0.00004033296,0.00005072727,0.001461472,0.01057607],"genre_scores_gemma":[0.8458222,0.000439989,0.1503192,0.00008904001,0.00005290172,0.00003222304,0.00007327383,0.00007671829,0.003094514],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0008311385,"threshold_uncertainty_score":0.002780378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03383541189135912,"score_gpt":0.3119009222650893,"score_spread":0.2780655103737302,"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."}}