{"id":"W2548054330","doi":"10.1109/aps.2016.7696717","title":"An FDTD-based adjoint sensitivity approach","year":2016,"lang":"en","type":"article","venue":"","topic":"Electromagnetic Simulation and Numerical Methods","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Finite-difference time-domain method; Sensitivity (control systems); Function (biology); Applied mathematics; Mathematics; Computer science; Algorithm; Physics; Electronic engineering; Optics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001792615,0.0000761696,0.00008903298,0.00003272479,0.00001574407,0.000008375557,0.00003174811,0.00003997493,0.0002934308],"category_scores_gemma":[0.0000308194,0.00004836146,0.00002825771,0.00008827199,0.00001746405,0.00005192859,0.000003159771,0.00003852908,0.00004136828],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002160072,"about_ca_system_score_gemma":0.000004634341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004388057,"about_ca_topic_score_gemma":0.000001205854,"domain_scores_codex":[0.9995006,0.00007959759,0.00008431329,0.0001096987,0.00007522903,0.0001505513],"domain_scores_gemma":[0.9995647,0.0001496531,0.000006138813,0.0001745557,0.00001635629,0.00008860912],"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":[0.0000131021,0.0000802337,0.0009976306,0.00001549118,0.00001074511,0.000002216019,0.00002197821,0.03124523,0.622871,0.00155847,0.0003875209,0.3427964],"study_design_scores_gemma":[0.0003147512,0.00008337474,0.0099757,0.000002940239,0.000003609288,0.000001699294,0.000003696854,0.9115677,0.07694275,0.0001759237,0.0007874403,0.0001404328],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1384476,0.000008691147,0.8452955,0.00009311992,0.00004947063,0.00005086651,9.475927e-7,0.0004826233,0.01557112],"genre_scores_gemma":[0.8800525,7.019706e-7,0.1196616,0.0001027084,0.0000366888,0.000004074443,0.000001208955,0.00001370733,0.0001268255],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8803225,"threshold_uncertainty_score":0.3212862,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01338385009303924,"score_gpt":0.2494270052537377,"score_spread":0.2360431551606985,"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."}}