{"id":"W2126386872","doi":"10.1109/aps.1996.549921","title":"Underground target probing using FDTD","year":2002,"lang":"en","type":"article","venue":"","topic":"Electromagnetic Simulation and Numerical Methods","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Finite-difference time-domain method; Detector; Ultra high frequency; Dipole; Finite difference method; Ground-penetrating radar; Field (mathematics); Discrete dipole approximation; Computer science; Wavelength; Radar; Optics; Physics; Acoustics; Scattering; Mathematics; Telecommunications","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":[0.0001292911,0.0002338275,0.0002297383,0.0002107,0.0002014706,0.000420797,0.0003084777,0.0005581393,0.001735154],"category_scores_gemma":[0.0004982174,0.000171064,0.0002534696,0.0002792724,0.0003008916,0.0004173928,0.0003636301,0.0003457404,0.0004432322],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003500227,"about_ca_system_score_gemma":0.0002638902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001651117,"about_ca_topic_score_gemma":0.0008647445,"domain_scores_codex":[0.999889,0.00002413849,0.000005160534,0.00001486585,0.00005761801,0.000009270856],"domain_scores_gemma":[0.9998239,0.00009529654,0.00001351449,0.00003259309,0.0000282849,0.000006508785],"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":[0.0001338323,0.00005859485,0.001189602,0.0002573671,0.000028947,0.0003308886,0.000467624,0.5202309,0.1650673,0.08136974,0.004711218,0.226154],"study_design_scores_gemma":[0.00001122459,0.00002255331,0.000126695,0.00001295183,0.000003636071,0.0001456753,0.00002048526,0.9665545,0.01642506,0.004285946,0.01238026,0.00001098473],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0176186,0.0002274901,0.9738216,0.000142331,0.00005545493,0.00001907071,0.0000736561,0.0006691754,0.007372747],"genre_scores_gemma":[0.4624221,0.0006833923,0.5299348,0.00006629226,0.00002058123,0.00006716825,0.0001666246,0.00008055363,0.006558427],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001735154,"threshold_uncertainty_score":0.005804658,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04260366540945147,"score_gpt":0.2556173193812662,"score_spread":0.2130136539718147,"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."}}