{"id":"W3171582658","doi":"10.1103/physrevb.104.155402","title":"Impact of nitrogen doping on the linear and nonlinear terahertz response of graphene","year":2021,"lang":"en","type":"preprint","venue":"Physical review. B./Physical review. B","topic":"Chemical and Physical Properties of Materials","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation; Compute Canada","keywords":"Graphene; Terahertz radiation; Doping; Materials science; Dipole; Condensed matter physics; Density functional theory; Nonlinear system; Nitrogen; Graphene nanoribbons; Chemical physics; Nanotechnology; Optoelectronics; Physics; Chemistry; Computational chemistry; Quantum mechanics","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":[0.0002950983,0.000364317,0.000297649,0.0004077272,0.0003067258,0.0004520977,0.0004852546,0.0004866147,0.001828232],"category_scores_gemma":[0.0009271001,0.0001810688,0.0002887215,0.0002973276,0.0006002864,0.0003803373,0.0003718942,0.0002464318,0.0002061837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005049533,"about_ca_system_score_gemma":0.0003213045,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004329051,"about_ca_topic_score_gemma":0.00449684,"domain_scores_codex":[0.9998329,0.00003390973,0.000003962603,0.00001492501,0.00007111232,0.00004320962],"domain_scores_gemma":[0.9996506,0.0002577875,0.00002214259,0.00002197227,0.00003297343,0.00001448386],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009083201,0.0001745271,0.00933157,0.0007749398,0.0002416434,0.00120033,0.0004228262,0.4922077,0.432679,0.04299845,0.000848793,0.0182119],"study_design_scores_gemma":[0.00006326089,0.0002950106,0.009091388,0.0001197702,0.0001283918,0.0002617335,0.0002878323,0.7797508,0.2012107,0.006095827,0.002623445,0.0000717658],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9821451,0.001071648,0.003701126,0.0002454654,0.00003546356,0.00001125342,0.0001000972,0.00007862931,0.01261126],"genre_scores_gemma":[0.99734,0.0004583958,0.0008765018,0.00003606439,0.000003740515,0.000006564363,0.00004314161,0.00002327848,0.00121237],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004329051,"threshold_uncertainty_score":0.008607686,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03559650733307242,"score_gpt":0.3780971745564132,"score_spread":0.3425006672233408,"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."}}