{"id":"W3007365918","doi":"10.1002/jnm.2733","title":"Recent advances in parametric modeling of microwave components using combined neural network and transfer function","year":2020,"lang":"en","type":"article","venue":"International Journal of Numerical Modelling Electronic Networks Devices and Fields","topic":"Microwave Engineering and Waveguides","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Transfer function; Parametric statistics; Artificial neural network; Computer science; Parametric model; Sensitivity (control systems); Microwave; Control theory (sociology); Algorithm; Electronic engineering; Artificial intelligence; Engineering; Mathematics","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":[0.0005236002,0.0005621618,0.0003989552,0.0004345276,0.0001320189,0.0005799991,0.0006965027,0.0005764109,0.0008966351],"category_scores_gemma":[0.0008371953,0.0002967013,0.0005592731,0.0004862806,0.0003151763,0.0008530957,0.0003199311,0.0005372969,0.0002960838],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004137312,"about_ca_system_score_gemma":0.0003204272,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002696228,"about_ca_topic_score_gemma":0.001885588,"domain_scores_codex":[0.9998233,0.00006269731,0.00001239877,0.00002707325,0.00006363571,0.00001090613],"domain_scores_gemma":[0.9997267,0.0001366239,0.0000322947,0.00002505827,0.00007192839,0.000007362032],"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":[0.00002272236,0.00001524527,0.0003144165,0.00006341119,0.00003146278,0.00003132299,0.00001640538,0.9556515,0.00281557,0.002799611,0.0001996187,0.03803865],"study_design_scores_gemma":[5.280917e-7,0.000004900222,0.00005289581,0.000002440516,0.0000025109,0.000004025228,0.000001082753,0.9987388,0.000318741,0.0004785903,0.0003936003,0.000001819549],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02486196,0.003867386,0.9653246,0.0002966002,0.00004547432,0.00001798753,0.0000505509,0.0003742741,0.005161311],"genre_scores_gemma":[0.8296338,0.007566807,0.1557574,0.0001035532,0.0001287293,0.0001106948,0.000157172,0.00009539694,0.006446385],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002696228,"threshold_uncertainty_score":0.005361021,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02005551600800605,"score_gpt":0.225737729391011,"score_spread":0.205682213383005,"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."}}