{"id":"W2028257783","doi":"10.1116/1.3605300","title":"Monte Carlo simulation of electron scattering and secondary electron emission in individual multiwalled carbon nanotubes: A discrete-energy-loss approach","year":2011,"lang":"en","type":"article","venue":"Journal of Vacuum Science & Technology B Nanotechnology and Microelectronics Materials Processing Measurement and Phenomena","topic":"Electron and X-Ray Spectroscopy Techniques","field":"Materials Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"University of British Columbia","keywords":"Scattering; Electron; Monte Carlo method; Secondary emission; Atomic physics; Electron scattering; Secondary electrons; Materials science; Carbon nanotube; Ionization; Range (aeronautics); Electron energy loss spectroscopy; Molecular physics; Computational physics; Physics; Nanotechnology; Optics; Ion; Nuclear physics; Composite material; 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":[0.0008954821,0.0004007293,0.0008003684,0.0005575348,0.0007112385,0.0007827254,0.001081923,0.0014646,0.001333362],"category_scores_gemma":[0.001902581,0.0005896846,0.0007122128,0.0006038253,0.0007521685,0.0006609263,0.0004003654,0.0006632718,0.000148454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001376215,"about_ca_system_score_gemma":0.001284096,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01033653,"about_ca_topic_score_gemma":0.006734804,"domain_scores_codex":[0.999761,0.00008106168,0.000008946918,0.00001740817,0.00008634372,0.00004522075],"domain_scores_gemma":[0.9984566,0.001132343,0.00009697845,0.00007644604,0.0001427406,0.00009486746],"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":[0.0000316691,0.00002074737,0.0003493284,0.00001370326,0.00001046575,0.00003184798,0.0000145184,0.9954569,0.0006658376,0.002741015,0.00003773221,0.0006262599],"study_design_scores_gemma":[0.000005171825,0.000004040875,0.00004141781,0.000001135996,0.000001456948,0.000003901319,0.000002060658,0.9994434,0.0001872661,0.0002709296,0.0000373539,0.000001835409],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.63674,0.0006927273,0.3467803,0.0005280895,0.00007614342,0.0001691353,0.0002700366,0.0004489115,0.01429463],"genre_scores_gemma":[0.9604671,0.0002578577,0.03602544,0.00007729494,0.00001510274,0.0001964691,0.0001484041,0.00008223022,0.002730177],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01033653,"threshold_uncertainty_score":0.02055269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01883530364204594,"score_gpt":0.2545814826173849,"score_spread":0.235746178975339,"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."}}