{"id":"W2099734720","doi":"10.1109/lpt.2006.882279","title":"An Efficient Bidirectional Propagation Method Based on Dirichlet-to-Neumann Maps","year":2006,"lang":"en","type":"article","venue":"IEEE Photonics Technology Letters","topic":"Electromagnetic Simulation and Numerical Methods","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Beam propagation method; Classification of discontinuities; Computation; Dirichlet distribution; Computer science; Mathematical analysis; Algorithm; Mathematics; Optics; Physics; Boundary value problem","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":[0.0004353649,0.0006490345,0.0004451121,0.0004391305,0.0005800375,0.0005818263,0.0008875892,0.0006399366,0.002995825],"category_scores_gemma":[0.0009691119,0.0003305981,0.0004281156,0.0003845728,0.000428023,0.0007985682,0.0008746622,0.000715794,0.0009360443],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003885518,"about_ca_system_score_gemma":0.0009486127,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001712417,"about_ca_topic_score_gemma":0.001902132,"domain_scores_codex":[0.9997794,0.00005956698,0.000007233196,0.00001512536,0.0001143695,0.00002424127],"domain_scores_gemma":[0.9996538,0.0001719076,0.00002238001,0.00004026201,0.00008587445,0.00002569434],"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":[0.0001708128,0.0001357124,0.0009234668,0.0003005837,0.00004430637,0.0002916706,0.0002799691,0.5115551,0.05932708,0.206353,0.00456178,0.2160565],"study_design_scores_gemma":[0.0000117281,0.00001906839,0.00004298744,0.000008701628,0.000004057894,0.00004212319,0.00001402551,0.9837288,0.005314605,0.006960706,0.00384089,0.00001226237],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005506951,0.00005446856,0.9908605,0.00003945018,0.00003430205,0.00003184834,0.00002883051,0.000227321,0.003216417],"genre_scores_gemma":[0.1789965,0.0003526174,0.8113285,0.00005042449,0.00002618354,0.0003610902,0.0001357507,0.0003007986,0.008447982],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002995825,"threshold_uncertainty_score":0.01002198,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005380987320401048,"score_gpt":0.2549594410217618,"score_spread":0.2495784537013608,"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."}}