{"id":"W4406276158","doi":"10.1109/mmm.2024.3486588","title":"Neuro-Impedance Function for Electromagnetic Modeling","year":2025,"lang":"en","type":"article","venue":"IEEE Microwave Magazine","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Electrical impedance; Function (biology); Computational electromagnetics; Electronic engineering; Computer science; Acoustics; Electromagnetic field; Engineering; Electrical engineering; Physics","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":[0.0003837292,0.0006985049,0.0004927234,0.0005949597,0.0002944806,0.0009315268,0.0007828362,0.001163308,0.002896022],"category_scores_gemma":[0.0009963333,0.0002287554,0.0007674551,0.0008197419,0.0005521254,0.001284026,0.0006408783,0.001412212,0.001336031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006384873,"about_ca_system_score_gemma":0.0005258477,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001658469,"about_ca_topic_score_gemma":0.001053242,"domain_scores_codex":[0.9997899,0.00006684578,0.00001159718,0.00003195136,0.00008685479,0.00001289217],"domain_scores_gemma":[0.9998364,0.00006794714,0.0000196287,0.000020139,0.0000498794,0.000005945791],"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":[0.00004346184,0.00003567309,0.0007140635,0.00037662,0.00007090247,0.000229804,0.0001438779,0.4886375,0.008664077,0.3444379,0.008736654,0.1479094],"study_design_scores_gemma":[0.000003414029,0.00001959906,0.0002267004,0.00005862967,0.00001347334,0.00008744205,0.00002522804,0.8987454,0.001293742,0.07475976,0.02475222,0.00001448714],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00239501,0.004041776,0.9796578,0.0007290025,0.00017063,0.00001660903,0.00009241184,0.0002188938,0.01267791],"genre_scores_gemma":[0.5057167,0.02614769,0.4171872,0.0008667193,0.0007833167,0.0004575905,0.0006086675,0.0003241509,0.04790802],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002896022,"threshold_uncertainty_score":0.009688139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01411256819920315,"score_gpt":0.2468716710617566,"score_spread":0.2327591028625534,"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."}}