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Cited article:

Machine learning-assisted identification of potential sources of bias in measurements of prompt-fission neutron spectra

Noah A.W. Walton, Denise Neudecker, Scott A. Vander Wiel, Michael J. Grosskopf and Keegan J. Kelly
Computer Physics Communications 315 109698 (2025)
https://doi.org/10.1016/j.cpc.2025.109698

Machine Learning to Select Experiments Driven by Fundamental Science and Applications for Targeted Nuclear Data Improvement

D. Neudecker, T. E. Cutler, M. Devlin, P. Brain, N. Gibson, M. J. Grosskopf, M. W. Herman, J. Hutchinson, T. Kawano, A. Khatiwada, N. Kleedtke, E. Leal-Cidoncha, R. C. Little, A. E. Lovell, A. Stamatopoulos, E. C. Thompson, S. A. Vander Wiel and E. Williamson
Physical Review X 15 (2) (2025)
https://doi.org/10.1103/PhysRevX.15.021086

Templates of expected measurement uncertainties

Denise Neudecker, Amanda M. Lewis, Eric F. Matthews, et al.
EPJ Nuclear Sciences & Technologies 9 35 (2023)
https://doi.org/10.1051/epjn/2023014

Templates of expected measurement uncertainties for (n, xn) cross sections

Jeffrey R. Vanhoy, Robert C. Haight, Sally F. Hicks, Matthew Devlin, Denise Neudecker, Michal Herman, Arjan Koning, Keegan J. Kelly, Ian Thompson, Cyrille De Saint Jean and Denise Neudecker
EPJ Nuclear Sciences & Technologies 9 31 (2023)
https://doi.org/10.1051/epjn/2023019