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Euclid: Modelling massive neutrinos in cosmology -- a code comparison, , , , , , , , , and 126 other author(s). (2022)cite arxiv:2211.12457Comment: 43 pages, 17 figures, 2 tables; published on behalf of the Euclid Consortium; data available at https://doi.org/10.5281/zenodo.7297976.Nanoseconds Timing System Based on IEEE 1588 FPGA Implementation., , , , , , , , , and 47 other author(s). CoRR, (2018)$Euclid$ preparation: XV. Forecasting cosmological constraints for the $Euclid$ and CMB joint analysis, , , , , , , , , and 199 other author(s). (2021)cite arxiv:2106.08346Comment: 19 pages, 8 figures, 4 tables, 1 appendix.Euclid preparation: V. Predicted yield of redshift 7<z<9 quasars from the wide survey, , , , , , , , , and 119 other author(s). (2019)cite arxiv:1908.04310Comment: Submitted to A&A. This paper has been internally reviewed by the Euclid Consortium.Interpretable machine learning approach for electron antineutrino selection in a large liquid scintillator detector., , , , , , , , , and 58 other author(s). CoRR, (2024)Running of the Charm-Quark Mass from HERA Deep-Inelastic Scattering Data, , , , , , , , , and 40 other author(s). (May 24, 2017)