{"id":"W2901232140","doi":"10.1109/tmtt.2018.2879014","title":"Iterative Loewner Matrix Macromodeling Approach for Noisy Frequency Responses","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Microwave Theory and Techniques","topic":"Lightning and Electromagnetic Phenomena","field":"Physics and Astronomy","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada; CMC Microsystems","keywords":"Matrix pencil; Singular value decomposition; Frequency domain; Iterative method; Algorithm; Singular value; Matrix decomposition; Orthonormal basis; Matrix (chemical analysis); Nonlinear system; Computer science; Sparse matrix; Mathematics; Mathematical analysis; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007030288,0.0008511483,0.0006472434,0.00054461,0.0003814079,0.0006285674,0.001106549,0.000968308,0.003158545],"category_scores_gemma":[0.001979644,0.000346589,0.0005800881,0.0003997518,0.0004806982,0.001484252,0.0005061139,0.001049286,0.001085831],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004709705,"about_ca_system_score_gemma":0.0006663876,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001442799,"about_ca_topic_score_gemma":0.002006225,"domain_scores_codex":[0.9996017,0.0001334658,0.00001907231,0.00006437782,0.0001609006,0.00002062843],"domain_scores_gemma":[0.9994828,0.0002487471,0.00006191657,0.00008233846,0.0001106855,0.0000134817],"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":[0.00007483213,0.00003867952,0.0003358371,0.0001486416,0.00004723313,0.0001397416,0.0002401503,0.8259341,0.03072577,0.03887971,0.0008841646,0.1025513],"study_design_scores_gemma":[0.000003623928,0.00002041128,0.00003060001,0.000007186219,0.000004386049,0.00002762249,0.000008194484,0.9904654,0.003496258,0.003764053,0.002165081,0.000007169065],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001055472,0.0000250102,0.9981765,0.00001519774,0.000005205542,0.000007915831,0.000007665214,0.0001471112,0.0005599629],"genre_scores_gemma":[0.1865389,0.000329052,0.8064907,0.00009456764,0.00003778802,0.0002465463,0.0001641814,0.0002469657,0.005851354],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003158545,"threshold_uncertainty_score":0.01056635,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01114200090120705,"score_gpt":0.2701148878448585,"score_spread":0.2589728869436514,"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."}}