{"id":"W2346780453","doi":"10.2528/pierb16012101","title":"THE FORWARD TRANSMISSION MATRIX (FTM) METHOD FOR S-PARAMETER ANALYSIS OF MICROWAVE CIRCUITS AND THEIR METAMATERIAL COUNTERPARTS","year":2016,"lang":"en","type":"article","venue":"Progress In Electromagnetics Research B","topic":"Metamaterials and Metasurfaces Applications","field":"Materials Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Taibah University","keywords":"Electronic circuit; Microwave; Metamaterial; Node (physics); Computer science; Network analysis; Microwave engineering; Electronic engineering; Matrix (chemical analysis); Electrical engineering; Topology (electrical circuits); Telecommunications; Physics; Engineering; Acoustics; Optics; Materials science","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":[0.006775672,0.0001962454,0.0005563536,0.0003378394,0.0002791103,0.0002395788,0.0005618599,0.0001117064,0.0001042364],"category_scores_gemma":[0.0002653218,0.00009966732,0.0001370206,0.0007257091,0.0005196137,0.0001040952,0.0001162966,0.00009765092,0.000004210091],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005028561,"about_ca_system_score_gemma":0.00009468872,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002556696,"about_ca_topic_score_gemma":0.00006491824,"domain_scores_codex":[0.9967209,0.0008262264,0.0006433621,0.0005195632,0.0004665776,0.0008233971],"domain_scores_gemma":[0.996529,0.002220429,0.0001807825,0.0005337807,0.0004080932,0.0001278695],"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":[0.0002086728,0.00006700892,0.000139066,0.00005614194,0.0001129857,4.218153e-7,0.0001954256,0.000001893445,0.9074975,0.002237325,0.00006814901,0.08941536],"study_design_scores_gemma":[0.0006195093,0.00053409,0.0007106222,0.0000338736,0.0001763201,0.000002801328,0.0000369765,0.002787163,0.9784832,0.006679943,0.009792995,0.0001425097],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9551157,0.005534833,0.0368293,0.0009239134,0.00008787947,0.001274284,0.0001765713,0.00002010933,0.00003742644],"genre_scores_gemma":[0.9671627,0.001500451,0.03020482,0.00000844588,0.00003990153,0.00087614,0.00001158589,0.00002839263,0.0001675326],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08927285,"threshold_uncertainty_score":0.4064315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04134106044633197,"score_gpt":0.3925315448028732,"score_spread":0.3511904843565413,"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."}}