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Ballester, F., Tedgren, A. C., Granero, D., Haworth, A., Mourtada, F., Fonseca, G. P., et al. (2015). A generic high-dose rate Ir-192 brachytherapy source for evaluation of model-based dose calculations beyond the TG-43 formalism. Med. Phys., 42(6), 3048–3062.
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Ma, Y. Z., Vijande, J., Ballester, F., Tedgren, A. C., Granero, D., Haworth, A., et al. (2017). A generic TG-186 shielded applicator for commissioning model-based dose calculation algorithms for high-dose-rate Ir-192 brachytherapy. Med. Phys., 44(11), 5961–5976.
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ATLAS Collaboration(Abat, E. et al), Bernabeu Verdu, J., Castillo Gimenez, V., Costa, M. J., Escobar, C., Ferrer, A., et al. (2011). A layer correlation technique for pion energy calibration at the 2004 ATLAS Combined Beam Test. J. Instrum., 6, P06001–35pp.
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LHCb Collaboration(Aaij, R. et al), Martinez-Vidal, F., Oyanguren, A., Ruiz Valls, P., & Sanchez Mayordomo, C. (2016). A new algorithm for identifying the flavour of B-s(0) mesons at LHCb. J. Instrum., 11, P05010–23pp.
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ANTARES and HESS Collaborations(Petroff, E. et al), Barrios-Marti, J., Hernandez-Rey, J. J., Illuminati, G., Lotze, M., Tönnis, C., et al. (2017). A polarized fast radio burst at low Galactic latitude. Mon. Not. Roy. Astron. Soc., 469(4), 4465–4482.
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Gammaldi, V., Zaldivar, B., Sanchez-Conde, M. A., & Coronado-Blazquez, J. (2023). A search for dark matter among Fermi-LAT unidentified sources with systematic features in machine learning. Mon. Not. Roy. Astron. Soc., 520(1), 1348–1361.
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Pierre Auger Collaboration(Abreu, P. et al), & Pastor, S. (2012). A search for point sources of EeV neutrons. Astrophys. J., 760(2), 148–11pp.
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Pierre Auger Collaboration(Aab, A. et al), & Pastor, S. (2014). A search for point sources of EeV photons. Astrophys. J., 789(2), 160–12pp.
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Pierre Auger Collaboration(Aab, A. et al), & Pastor, S. (2014). A targeted search for point sources of EeV neutrons. Astrophys. J. Lett., 789(2), L34–7pp.
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NEXT Collaboration(Simon, A. et al), Gomez-Cadenas, J. J., Alvarez, V., Benlloch-Rodriguez, J. M., Botas, A., Carcel, S., et al. (2017). Application and performance of an ML-EM algorithm in NEXT. J. Instrum., 12, P08009–22pp.
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