{"id":"W3003663007","doi":"","title":"Recent Advances in EM Parametric Modeling Using Combined Neural Network and Transfer Function","year":2019,"lang":"en","type":"article","venue":"International Symposium on Antennas and Propagation","topic":"Microwave Engineering and Waveguides","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Transfer function; Artificial neural network; Computer science; Parametric statistics; Parametric model; Antenna (radio); Wideband; Computational electromagnetics; Data modeling; Function (biology); Artificial intelligence; Electronic engineering; Engineering; Telecommunications; Physics; Electromagnetic field; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001214602,0.0001129997,0.0001057273,0.0001114644,0.00002570435,0.00005425315,0.00003787335,0.00004872679,0.00001208857],"category_scores_gemma":[0.000006581387,0.0001080716,0.00001720744,0.0001453206,0.000006975242,0.0002280762,0.00000806732,0.0001147375,0.000002840574],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004790437,"about_ca_system_score_gemma":0.00000320984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005915301,"about_ca_topic_score_gemma":0.00001134756,"domain_scores_codex":[0.9993945,0.00001391167,0.000192024,0.0001595719,0.0001127063,0.0001272642],"domain_scores_gemma":[0.9998387,0.00002472198,0.00001335779,0.0000518831,0.00004090756,0.00003040254],"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":[0.00007533146,0.00001097071,0.002024448,0.00003465907,0.00001276751,0.000001021667,0.00006830793,0.9754971,0.005726818,0.001097864,0.000003349225,0.01544731],"study_design_scores_gemma":[0.0004307447,0.00007713492,0.001343885,0.0001022799,0.000005735611,0.000007200136,0.00002807747,0.9967599,0.0001944666,0.0002999654,0.0006250408,0.0001255634],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9532991,0.00209051,0.04303036,0.00009140483,0.0008774928,0.0001692914,0.000002761807,0.00006447726,0.0003746099],"genre_scores_gemma":[0.9957361,0.003937284,0.0001279473,0.0000460355,0.0000911653,0.000005761964,0.00001865846,0.00001691829,0.00002018279],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04290241,"threshold_uncertainty_score":0.4407033,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01163154096538498,"score_gpt":0.2173523535339802,"score_spread":0.2057208125685952,"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."}}