{"id":"W2026248553","doi":"10.1109/aps.2006.1711353","title":"Comparison of Three FDTD Modeling Techniques for Coaxial Feed","year":2006,"lang":"en","type":"article","venue":"2006 IEEE Antennas and Propagation Society International Symposium","topic":"Electromagnetic Simulation and Numerical Methods","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Finite-difference time-domain method; Discretization; Coaxial; Electrical conductor; Conductor; Finite difference method; Acoustics; Numerical modeling; Electronic engineering; Transmission line; Antenna (radio); Computational electromagnetics; Computer science; Optics; Physics; Electromagnetic field; Materials science; Engineering; Electrical engineering; Mathematics; Telecommunications; Mathematical analysis","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":[0.0001731862,0.0001191961,0.0001844855,0.00002903503,0.00007346869,0.00003343008,0.00008839995,0.00009294434,0.00001452051],"category_scores_gemma":[0.000009125803,0.0001153598,0.0001135271,0.00009211714,0.00004049475,0.0001044716,0.000009317704,0.00008444189,9.113351e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003653434,"about_ca_system_score_gemma":0.000008415345,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000540307,"about_ca_topic_score_gemma":0.00001035976,"domain_scores_codex":[0.9991534,0.00001290159,0.000377132,0.0001394119,0.0001815463,0.0001355472],"domain_scores_gemma":[0.9995335,0.00007631535,0.00007600416,0.00006795382,0.0002187096,0.00002747713],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007654847,0.000144845,0.00613075,0.0001522315,0.0001178267,1.872135e-7,0.0003736651,0.07745705,0.8918713,0.002970239,0.004045084,0.01666032],"study_design_scores_gemma":[0.0003158429,0.00008475302,0.0003464461,0.00002424923,0.00001802104,0.000001478433,0.00003445998,0.9315666,0.06460793,0.001396969,0.001474408,0.0001288762],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1350912,0.0002032198,0.8619761,0.000412148,0.0003199609,0.0003065812,0.00002970194,0.0001505608,0.001510504],"genre_scores_gemma":[0.9649907,0.00006687142,0.03433781,0.00005888403,0.0002958336,0.00004534766,0.00005742189,0.00001998186,0.0001271871],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8541095,"threshold_uncertainty_score":0.4704235,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02319838130069525,"score_gpt":0.3039294306940955,"score_spread":0.2807310493934003,"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."}}