{"id":"W2013561562","doi":"10.1109/aps.2013.6711110","title":"A surface impedance boundary condition approach to the FDTD modeling of graphene","year":2013,"lang":"en","type":"article","venue":"","topic":"Electromagnetic Simulation and Numerical Methods","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Finite-difference time-domain method; Graphene; Boundary value problem; Electrical impedance; Materials science; Range (aeronautics); Surface (topology); Boundary (topology); Graphene nanoribbons; Computer science; Electronic engineering; Optics; Nanotechnology; Physics; Mathematics; Electrical engineering; Mathematical analysis; Engineering; Composite material; Geometry","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":[0.0001219553,0.00006950788,0.00009920404,0.00002279038,0.00003758439,0.00001810038,0.00008814718,0.00002792759,0.0001357038],"category_scores_gemma":[0.00001977155,0.00004837462,0.00003355066,0.0002286917,0.00001444691,0.00005814662,0.00001056729,0.00006750633,0.00002822159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009576653,"about_ca_system_score_gemma":0.00000476296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005514395,"about_ca_topic_score_gemma":0.000001072776,"domain_scores_codex":[0.9995071,0.00003272733,0.0001506334,0.00008272834,0.00009675758,0.0001300442],"domain_scores_gemma":[0.9996905,0.00006206254,0.00001095265,0.0001476389,0.00004322806,0.0000455868],"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":[0.000001441012,0.000009492623,0.00001509634,0.00001347432,0.000008387054,1.872176e-8,0.0001375051,0.9780256,0.01523598,0.0008711139,0.0005886863,0.005093156],"study_design_scores_gemma":[0.00007859551,0.00002832089,0.0004099654,0.000003640445,0.000004118756,0.000001099655,0.00006033575,0.9955465,0.001857097,0.001650831,0.0002914617,0.00006807579],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4360406,0.0001990757,0.5497882,0.00009024113,0.0000447204,0.000171127,7.216854e-7,0.00008062822,0.01358471],"genre_scores_gemma":[0.9013297,0.00001272039,0.09836435,0.0001225042,0.00001659529,0.00001767331,0.000002176475,0.00001087296,0.0001234031],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4652891,"threshold_uncertainty_score":0.197266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01762566948533451,"score_gpt":0.2582310935171527,"score_spread":0.2406054240318182,"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."}}