{"id":"W4399118887","doi":"10.1109/tmtt.2024.3400152","title":"A Novel EM Parametric Modeling Method of Microwave Filters Incorporating Multivalued Neural Networks and Transfer Functions","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Microwave Theory and Techniques","topic":"Radio Wave Propagation Studies","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Key Research and Development Project of Hainan Province; Natural Science Foundation of Jiangsu Province; National Natural Science Foundation of China","keywords":"Transfer function; Microwave; Artificial neural network; Parametric statistics; Electronic engineering; Computer science; Control theory (sociology); Mathematics; Engineering; Artificial intelligence; Telecommunications; Electrical engineering","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":[0.0002998569,0.0005628336,0.0002889068,0.0004311405,0.0002396407,0.0004033096,0.0007904861,0.000516076,0.001440297],"category_scores_gemma":[0.0004154573,0.0002643984,0.0006924929,0.0003141868,0.0002333485,0.0009108055,0.0002919685,0.0005384348,0.0004376328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005374551,"about_ca_system_score_gemma":0.0004528236,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002771317,"about_ca_topic_score_gemma":0.003026435,"domain_scores_codex":[0.9998558,0.0000262622,0.000007777631,0.00003842637,0.00006239953,0.000009320119],"domain_scores_gemma":[0.999904,0.00002797706,0.00001505361,0.00001310991,0.00003594162,0.000003813891],"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":[0.00006059057,0.00003336668,0.000674945,0.0001149485,0.00006008827,0.0001033173,0.00009713079,0.705047,0.03802621,0.02207995,0.001298403,0.2324041],"study_design_scores_gemma":[0.000001257793,0.000009212207,0.00006137282,0.000003463897,0.000005629495,0.00002912793,0.000003763049,0.9947678,0.002458879,0.001176328,0.001478654,0.000004444324],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001966427,0.00006682239,0.9968795,0.00002437275,0.00001051284,0.000007709234,0.00001278173,0.00016433,0.0008675665],"genre_scores_gemma":[0.3925874,0.000629439,0.5961323,0.0001080902,0.00006236559,0.0001750096,0.0001937608,0.0001623831,0.009949243],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002771317,"threshold_uncertainty_score":0.00551039,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01958378168694369,"score_gpt":0.2553782138721686,"score_spread":0.2357944321852249,"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."}}