{"id":"W2101981096","doi":"10.1109/3.937391","title":"A wavelet formulation of the finite-difference method: full-vector analysis of optical waveguide junctions","year":2001,"lang":"en","type":"article","venue":"IEEE Journal of Quantum Electronics","topic":"Electromagnetic Simulation and Numerical Methods","field":"Engineering","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Curl (programming language); Finite difference method; Stencil; Finite-difference time-domain method; Waveguide; Maxwell's equations; Beam propagation method; Wavelet; Boundary value problem; Boundary (topology); Finite difference; Computer science; Mathematical analysis; Mathematics; Physics; Topology (electrical circuits); Optics; Computational science; Refractive index","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":[0.0006911996,0.0002535346,0.0003634783,0.0002264277,0.0001646391,0.0004530248,0.0006281623,0.0005988388,0.0008302084],"category_scores_gemma":[0.0008632639,0.0001962594,0.000309433,0.0002710843,0.0004198137,0.000578683,0.0003932007,0.0006426702,0.0002409877],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002796604,"about_ca_system_score_gemma":0.0005994756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001274664,"about_ca_topic_score_gemma":0.000951994,"domain_scores_codex":[0.9998699,0.00003683662,0.000006618054,0.000009954089,0.00006380714,0.00001277022],"domain_scores_gemma":[0.9997911,0.00008156181,0.00002061097,0.00002356578,0.00006984266,0.000013346],"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":[0.00008254686,0.00007529055,0.0006294196,0.0001662456,0.00002396027,0.0001356026,0.0001314617,0.7420697,0.07138293,0.1397816,0.000718583,0.0448027],"study_design_scores_gemma":[0.000005789858,0.00001278903,0.00004268883,0.000003665994,0.000001184962,0.00001003859,0.000004527623,0.9948955,0.002563663,0.00183662,0.0006190288,0.000004461368],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02416679,0.00009625625,0.9740837,0.00008213885,0.00002949951,0.00002193096,0.00003287044,0.0000683911,0.00141849],"genre_scores_gemma":[0.3118496,0.0003662111,0.6843392,0.00005947875,0.00002897663,0.0001398293,0.0001016863,0.00009477822,0.003020365],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001274664,"threshold_uncertainty_score":0.003655493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02384744983779893,"score_gpt":0.299425949491213,"score_spread":0.2755784996534141,"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."}}