{"id":"W4385705720","doi":"10.4208/cicp.oa-2021-0209","title":"Frozen Gaussian Approximation for the Dirac Equation in Curved Space with Application to Strained Graphene","year":2023,"lang":"en","type":"article","venue":"Communications in Computational Physics","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Carleton University; Montfort Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; National Science Foundation","keywords":"Graphene; Gaussian; Space (punctuation); Dirac equation; Physics; Dirac (video compression format); Mathematical physics; Mathematical analysis; Mathematics; Quantum mechanics; Computer science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007237542,0.0004921155,0.0004338569,0.00058561,0.0005031689,0.0007899947,0.001228307,0.001040602,0.001531929],"category_scores_gemma":[0.001772051,0.000217066,0.0005731232,0.0006348317,0.001115645,0.001077659,0.0007522291,0.0008479576,0.0004214682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007343003,"about_ca_system_score_gemma":0.0009945717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006325768,"about_ca_topic_score_gemma":0.005594542,"domain_scores_codex":[0.9998268,0.00006369398,0.000007377066,0.00001476042,0.00006130153,0.00002603882],"domain_scores_gemma":[0.9994723,0.0002332019,0.00003297381,0.0000903139,0.0001231911,0.00004797395],"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":[0.00004696729,0.00003568278,0.0004209685,0.00005912919,0.00002486842,0.000218198,0.0001168378,0.6946403,0.004489864,0.2907796,0.0005863422,0.00858127],"study_design_scores_gemma":[0.00000210175,0.000004112545,0.00002795445,0.000003036217,0.000001086726,0.000009296513,0.000007735002,0.9849365,0.0002319956,0.01458892,0.0001837864,0.000003473499],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06599741,0.0004470815,0.9266941,0.0003328199,0.00008094586,0.00004283692,0.00008187675,0.0002722996,0.006050756],"genre_scores_gemma":[0.6912795,0.001033469,0.3002878,0.0003170265,0.00006651329,0.0001445021,0.0001775754,0.0002241873,0.006469475],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006325768,"threshold_uncertainty_score":0.01257795,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05217953630946944,"score_gpt":0.3186634875438501,"score_spread":0.2664839512343807,"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."}}