Gamma Neutron Radioactive Source Identification in Water Cherenkov Detectors
This study demonstrates the feasibility of identifying and discriminating between gamma and neutron sources in Water Cherenkov Detectors by integrating statistical energy thresholding with an ensemble machine learning model, achieving an accuracy of 0.816 for enhanced radiation identification in nuclear security applications.