{"id":"W1029264492","doi":"","title":"A Spatially-filtered Finite-difference Time-domain Method with Controllable Stability Beyond the Courant Limit","year":2012,"lang":"en","type":"dissertation","venue":"Library and Archives Canada (Government of Canada)","topic":"Electromagnetic Simulation and Numerical Methods","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Finite-difference time-domain method; Limit (mathematics); Stability (learning theory); Spatial filter; Algorithm; Frequency domain; Mathematics; Domain (mathematical analysis); Finite difference; Finite difference method; Computer science; Mathematical analysis; Optics; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004189229,0.0003254862,0.0004806772,0.00002068759,0.0001347102,0.0000286334,0.0002391833,0.00006215124,0.0002906725],"category_scores_gemma":[0.00001121085,0.0002345603,0.00003853943,0.0001072741,0.00004605582,0.0001064307,0.00002513373,0.0003015692,7.272115e-9],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001207062,"about_ca_system_score_gemma":0.0007414678,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001243304,"about_ca_topic_score_gemma":0.02701616,"domain_scores_codex":[0.9976407,0.0002283911,0.0003586284,0.0002312061,0.00116456,0.0003764764],"domain_scores_gemma":[0.9976107,0.001714247,0.0001602072,0.0002851708,0.000001782774,0.0002278513],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.008542257,0.0002110323,0.008826911,0.002741469,0.001727566,0.00007672951,0.002662336,0.01186087,0.7648663,0.02301699,0.001308441,0.1741591],"study_design_scores_gemma":[0.003677039,0.0009645626,0.1701299,0.0005727682,0.0006047493,0.00001700016,0.005242543,0.2539364,0.5201625,0.007699002,0.03447025,0.002523324],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4267479,0.00384966,0.01404292,0.00260199,0.001008791,0.001792562,0.0009754052,0.000125408,0.5488554],"genre_scores_gemma":[0.9658671,0.00009360179,0.02258062,0.0004780933,0.00008682328,0.00004899802,0.000123166,0.00007729337,0.01064428],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5391192,"threshold_uncertainty_score":0.9907383,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004089614794052733,"score_gpt":0.1660074445024466,"score_spread":0.1619178297083939,"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."}}