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N. Walton

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Open access Aug 2026

Resolving root causes of experiment discrepancies guided by machine learning

Scientists rely on accurate experimental data to explain nature and then harness this knowledge for applications addressing human needs. However, discrepancies between experiments of the same observable can impede scientific progress if one does not understand the underlying causes. Here, we developed a process that un...

D. Neudecker, K. Kelly, S. Vander Wiel et al. · 0 citations
Review Open access 2026

Consistent quantification of energy uncertainties in experimental time-of-flight nuclear data across resolved, unresolved, and fast regimes

A major task for nuclear data evaluations is the curation of measurement data to be used in the inference of nuclear data quantities. The quality of the resulting measurement data uncertainty depends on the rigor of the evaluator reviewing the data set and the uncertainty information provided by the experimenter. Nucle...

N. Walton, Denise Neudecker, A. Khatiwada · 0 citations

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