{"id":"W2118742119","doi":"10.1109/mwsym.2000.863553","title":"Development of three-dimensional unconditionally stable finite-difference time-domain methods","year":2002,"lang":"en","type":"article","venue":"","topic":"Electromagnetic Simulation and Numerical Methods","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Finite-difference time-domain method; Computation; Stability (learning theory); Numerical stability; Computer science; Finite difference method; Dispersion (optics); Finite difference; Applied mathematics; Time domain; Computational electromagnetics; Numerical analysis; Algorithm; Mathematics; Computational science; Mathematical analysis; Electromagnetic field; Physics; Optics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002906747,0.0001327091,0.000204389,0.00008128153,0.00004661115,0.000008023653,0.0001007926,0.00006126741,0.01194328],"category_scores_gemma":[0.00006670084,0.0001194355,0.00004215696,0.0002420734,0.00003060917,0.00003855458,0.00002349515,0.00009773836,0.0001609849],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003686425,"about_ca_system_score_gemma":0.00001710389,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001844768,"about_ca_topic_score_gemma":0.000003771474,"domain_scores_codex":[0.9990477,0.0000665816,0.0003341933,0.0001373455,0.0002067966,0.000207398],"domain_scores_gemma":[0.9990426,0.0006565919,0.00003183798,0.0001344085,0.00005173022,0.00008279443],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001752832,0.0002088715,0.0002916825,0.00007436935,0.0001659778,0.000003351851,0.000367607,0.05748647,0.6184799,0.00404187,0.002913245,0.3159491],"study_design_scores_gemma":[0.0004887452,0.00007455399,0.005112027,0.0000227497,0.00001112698,0.000003548933,0.000007411852,0.9044394,0.07288777,0.007824619,0.008800104,0.000327882],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1200149,0.000253975,0.8587517,0.00005048173,0.00009984502,0.000117752,0.000004426318,0.0002208649,0.0204861],"genre_scores_gemma":[0.05481566,0.000001999602,0.9431834,0.00007484452,0.00001551676,0.00001222627,0.000009603487,0.00001789893,0.001868804],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.846953,"threshold_uncertainty_score":0.9889599,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0322600404090251,"score_gpt":0.2783950081706069,"score_spread":0.2461349677615818,"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."}}