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ISSN 2575-6206
Original article
Vol. 9, Issue 4, 2025November 14, 2025 CDT

A Machine Learning approach to enhance the classification of dark matter signals

Aaron Pinto, Juliana Caulkins, Anita Shaw,
Dark matterWeakly Interacting Massive ParticlesWIMPsRadiogenic neutronsDirect detection experimentsEnsemble learningVoting classifierSupport Vector MachineXGBoostFeature importance
Copyright Logoccby-nc-sa-4.0 • https://doi.org/10.64336/001c.147389
Journal of High School Science
Pinto, Aaron, Juliana Caulkins, and Anita Shaw. 2025. “A Machine Learning Approach to Enhance the Classification of Dark Matter Signals.” Journal of High School Science 9 (4): 192–208. https:/​/​doi.org/​10.64336/​001c.147389.

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