{"id":"W2046133867","doi":"10.1117/12.566468","title":"Time domain simulation of photonic crystals using the transmission line matrix method","year":2004,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Electromagnetic Simulation and Numerical Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Finite-difference time-domain method; Photonic crystal; Transmission-line matrix method; Polygon mesh; Computer science; Transmission line; Computation; Grid; Plane wave expansion; Computational science; Matrix (chemical analysis); Transmission (telecommunications); Plane wave expansion method; Electronic engineering; Algorithm; Computational electromagnetics; Optics; Materials science; Mathematics; Physics; Telecommunications; Geometry; Engineering","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":[0.0003324578,0.000270826,0.0003545638,0.0002034982,0.0003427627,0.0005373092,0.0005045946,0.000659034,0.002510986],"category_scores_gemma":[0.0009217387,0.0002349223,0.0004748794,0.0003247162,0.0003516311,0.0006344839,0.0004002048,0.0004941155,0.0003607711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004531114,"about_ca_system_score_gemma":0.0008504867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003565808,"about_ca_topic_score_gemma":0.002353845,"domain_scores_codex":[0.9998181,0.00005968973,0.000008536589,0.00001444881,0.0000823357,0.00001674504],"domain_scores_gemma":[0.9996489,0.0002237304,0.00002757092,0.00003522663,0.00005183963,0.0000127879],"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":[0.00003857344,0.00003912457,0.0002670387,0.00006205932,0.00001582957,0.00009561586,0.00007566153,0.9441608,0.01123277,0.03178271,0.0006442799,0.01158561],"study_design_scores_gemma":[0.000005716894,0.00000545178,0.00001792254,0.000001848102,9.286504e-7,0.000007778928,0.000003762319,0.9976202,0.000925792,0.0007153592,0.0006932272,0.000002039106],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05213705,0.0001852851,0.9323083,0.0002465552,0.00006503968,0.00008032125,0.0001927266,0.0006768616,0.01410796],"genre_scores_gemma":[0.4572966,0.0004290117,0.5354494,0.00006901121,0.00002866327,0.0003618371,0.000232976,0.0001823653,0.005950132],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003565808,"threshold_uncertainty_score":0.008400142,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01382776006304247,"score_gpt":0.2848697972336223,"score_spread":0.2710420371705798,"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."}}