{"id":"W2042418076","doi":"10.1002/jnm.670","title":"A S<scp>PICE</scp>analog behavioral model of two‐port devices with arbitrary port impedances based on the<i>S</i>‐parameters extracted from time‐domain field responses","year":2007,"lang":"en","type":"article","venue":"International Journal of Numerical Modelling Electronic Networks Devices and Fields","topic":"Electromagnetic Compatibility and Noise Suppression","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Flex (Canada); University of Victoria","funders":"","keywords":"Port (circuit theory); Behavioral modeling; Spice; Transient (computer programming); Electronic engineering; Electrical impedance; Field (mathematics); Time domain; Computer science; Equivalent circuit; Domain (mathematical analysis); Scattering parameters; Electrical engineering; Voltage; Engineering; Mathematics","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":[0.0001795566,0.0003471217,0.0002649904,0.0002905681,0.0001725826,0.0005170307,0.0005557386,0.000446489,0.002765567],"category_scores_gemma":[0.0004898487,0.0002022802,0.0003632866,0.0002027183,0.0004843597,0.0005777538,0.00020526,0.000379065,0.0006310218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003664412,"about_ca_system_score_gemma":0.0003288111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001326941,"about_ca_topic_score_gemma":0.001201926,"domain_scores_codex":[0.9999076,0.00002075142,0.000003886783,0.00001192064,0.00004780135,0.00000793058],"domain_scores_gemma":[0.9998443,0.00004068881,0.00001937259,0.00005575914,0.00003431049,0.000005416571],"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":[0.00007207329,0.00005806283,0.0007714448,0.0001298739,0.00003518841,0.0002655352,0.0001393249,0.8261905,0.08716599,0.05703335,0.002106266,0.02603235],"study_design_scores_gemma":[0.000003199226,0.00001348145,0.00008498678,0.00000285054,0.00000326202,0.00003519103,0.000004082035,0.9906141,0.006340609,0.001563323,0.001331882,0.000003032354],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0698528,0.00009170465,0.9131683,0.0001203305,0.00005121764,0.00006311803,0.0002150737,0.001624501,0.01481288],"genre_scores_gemma":[0.8526477,0.0001993963,0.1352558,0.0001039742,0.00002470538,0.0001907918,0.0002536506,0.0001804876,0.01114357],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002765567,"threshold_uncertainty_score":0.009251714,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01314839839018975,"score_gpt":0.2474570042587624,"score_spread":0.2343086058685726,"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."}}