{"id":"W1873215934","doi":"10.1109/aps.1999.789394","title":"Comparative study of lossy dielectric wedge diffraction for radio wave propagation modeling using UTD and FDTD","year":2003,"lang":"en","type":"article","venue":"","topic":"Electromagnetic Simulation and Numerical Methods","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Finite-difference time-domain method; Diffraction; Lossy compression; Wedge (geometry); Dielectric; Optics; Uniform theory of diffraction; Reflection (computer programming); Ray tracing (physics); Radio propagation; Radio wave; Materials science; Plane wave; Acoustics; Wave propagation; Physics; Telecommunications; Computer science; Optoelectronics","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":[0.0001474257,0.00009197491,0.0001916583,0.00008373393,0.0000512084,0.00001120338,0.00001673926,0.00003507303,0.00001124088],"category_scores_gemma":[0.00004857027,0.00008357763,0.00002050862,0.0002198395,0.000007749119,0.00008076829,0.00000273547,0.00006523852,2.908489e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003918229,"about_ca_system_score_gemma":0.000007512084,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001021712,"about_ca_topic_score_gemma":0.000003497421,"domain_scores_codex":[0.9994102,0.0000698657,0.0002086295,0.0001147597,0.00007645262,0.0001200868],"domain_scores_gemma":[0.9996666,0.0001399209,0.00003234223,0.00006588241,0.00006219343,0.00003305607],"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":[0.00007881528,0.0003272862,0.0006707461,0.0001079705,0.0001138133,4.478767e-7,0.002230128,0.8723036,0.1110196,0.001787521,0.00001088194,0.01134919],"study_design_scores_gemma":[0.0006919624,0.000333517,0.0005722952,0.000004983851,0.00003379402,0.000002781119,0.0003066777,0.9877194,0.00985811,0.0003642303,0.00001622263,0.00009602635],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5530824,0.0001136146,0.4458037,0.000001506576,0.00003923768,0.0003560552,1.837461e-7,0.0000312422,0.0005720757],"genre_scores_gemma":[0.9711431,0.000009814826,0.02875921,0.000003474663,0.00001587508,0.00001847774,0.00000101963,0.00001192055,0.00003706356],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4180607,"threshold_uncertainty_score":0.3408197,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07539196540783676,"score_gpt":0.3261834639960875,"score_spread":0.2507914985882507,"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."}}