{"id":"W1570920994","doi":"","title":"Electromagnetic wave propagation modeling in a complex environment using uniform geometrical theory of diffraction","year":2015,"lang":"en","type":"article","venue":"European Conference on Antennas and Propagation","topic":"Millimeter-Wave Propagation and Modeling","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Communications Research Centre Canada; Université du Québec en Outaouais","funders":"","keywords":"Diffraction; Ray tracing (physics); Uniform theory of diffraction; MATLAB; Wave propagation; Radio propagation model; Wideband; Wireless; Computer science; Radio propagation; Electromagnetic radiation; Finite-difference time-domain method; Acoustics; Channel (broadcasting); Optics; Electronic engineering; Tracing; Computational physics; Physics; Telecommunications; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007402232,0.0001730642,0.0001865435,0.0003273838,0.00004564974,0.00004552516,0.00006163437,0.00004532708,0.00003129353],"category_scores_gemma":[0.00005663176,0.0001601356,0.00002780298,0.0002004449,0.00003949717,0.0001828021,0.00002812921,0.0001898412,0.00001271952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001089622,"about_ca_system_score_gemma":0.0000252522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009757203,"about_ca_topic_score_gemma":0.000002817754,"domain_scores_codex":[0.9987233,0.0001981379,0.0004161001,0.0002262302,0.0002368702,0.0001993962],"domain_scores_gemma":[0.999563,0.00002065967,0.00009014556,0.00014242,0.00008954514,0.00009417678],"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":[0.000288733,0.0001874067,0.0001951062,0.0001921819,0.00003395798,0.00001805852,0.002183932,0.1791794,0.6802594,0.004447744,0.00000767254,0.1330064],"study_design_scores_gemma":[0.000564981,0.0002530847,0.0009546782,0.00008428222,0.00001387343,0.00001200758,0.000302137,0.9924766,0.004092853,0.001043033,0.00001994153,0.0001825331],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5197255,0.00007397994,0.4766613,0.00002782958,0.00003528488,0.0002287527,0.000002301812,0.00004541092,0.003199638],"genre_scores_gemma":[0.9970916,0.0002133693,0.002529066,0.00002624492,0.00003556212,0.000005411313,0.00003805816,0.00003166635,0.00002902946],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8132972,"threshold_uncertainty_score":0.6530139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1457352190680083,"score_gpt":0.2466746657458168,"score_spread":0.1009394466778084,"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."}}