{"id":"W4300263328","doi":"10.1007/978-3-031-01695-0_2","title":"A Numerical Interface Between FDTD and Haar MRTD: Formulation and Applications","year":2007,"lang":"en","type":"book-chapter","venue":"Synthesis lectures on computational electromagnetics","topic":"Electromagnetic Simulation and Numerical Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Finite-difference time-domain method; Haar; Interface (matter); Haar wavelet; Mathematics; Wavelet; Computer science; Algorithm; Mathematical analysis; Physics; Optics; Wavelet transform; Discrete wavelet transform; Mechanics; Artificial intelligence","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001943978,0.0005435865,0.0005656059,0.0003811751,0.0001577538,0.00008512756,0.0001499791,0.0004501207,0.0001662385],"category_scores_gemma":[0.00008858588,0.0005695275,0.00009843372,0.0001257665,0.0001071407,0.00004482052,0.0000315238,0.000650097,0.00002919743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000128745,"about_ca_system_score_gemma":0.00003890075,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002416173,"about_ca_topic_score_gemma":0.000002219325,"domain_scores_codex":[0.9980704,0.00004814709,0.000545257,0.0005076871,0.0004387604,0.0003897837],"domain_scores_gemma":[0.9966648,0.002658824,0.0001298517,0.0002232158,0.0001065422,0.0002167392],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00007758266,0.00003692285,0.00003848641,0.0002517414,0.0003346771,0.000004879942,0.00008940929,0.06334902,0.0006419285,0.06753196,0.0006476144,0.8669958],"study_design_scores_gemma":[0.001184157,0.003084387,0.007382663,0.0004117491,0.0008851573,0.0001631627,0.00000645645,0.3251282,0.004518031,0.4656334,0.1883283,0.003274385],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00208253,0.009001812,0.7993716,0.0004504183,0.0001287382,0.001472116,0.00008590236,0.0007867212,0.1866202],"genre_scores_gemma":[0.910453,0.0008514406,0.07978342,0.0005114682,0.0008872864,0.0001304251,0.0001897489,0.0003987727,0.006794493],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9083704,"threshold_uncertainty_score":0.9996756,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01819272768014808,"score_gpt":0.2743870389667077,"score_spread":0.2561943112865596,"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."}}