{"id":"W2122240030","doi":"10.1109/ccece.2007.171","title":"A New Dynamic Local Mesh Refinement Algorithm for Finite Difference Time Domain","year":2007,"lang":"en","type":"article","venue":"","topic":"Electromagnetic Simulation and Numerical Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Finite-difference time-domain method; Algorithm; Computer science; Finite difference method; Mode (computer interface); Domain (mathematical analysis); Mesh generation; Finite element method; Mathematics; Engineering; Structural engineering; Physics","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":[0.0005359851,0.0005043335,0.0006866623,0.0006253792,0.0004230748,0.0005723952,0.001660959,0.0007035733,0.003987662],"category_scores_gemma":[0.001328642,0.0003270211,0.0006572154,0.0007264125,0.0004039813,0.001062277,0.0008892798,0.001046018,0.001696977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004142421,"about_ca_system_score_gemma":0.0006135625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00168767,"about_ca_topic_score_gemma":0.002392653,"domain_scores_codex":[0.9994455,0.00007855216,0.00002975181,0.00006657868,0.0003528087,0.00002674836],"domain_scores_gemma":[0.9995166,0.0001496254,0.00003414661,0.00007469202,0.0002012227,0.00002363528],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001456086,0.00007481478,0.0008782819,0.0003417164,0.00008434184,0.0002043617,0.0001954573,0.1432178,0.09500048,0.04416035,0.009473819,0.7062231],"study_design_scores_gemma":[0.00003832236,0.00005174864,0.0001708292,0.00001747389,0.00002039291,0.0002308396,0.00001754673,0.9468863,0.01683369,0.004765576,0.03093782,0.00002947466],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.000548334,0.00006253699,0.9986334,0.0000218183,0.00003608582,0.00001409873,0.00001037948,0.0002498535,0.0004233999],"genre_scores_gemma":[0.02354154,0.000201079,0.9729427,0.0000666733,0.00003926832,0.0001219003,0.0001556419,0.0001734601,0.002757762],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003987662,"threshold_uncertainty_score":0.01334006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007659208107756222,"score_gpt":0.2647757809941494,"score_spread":0.2571165728863932,"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."}}