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tokens: ACKNOWLEDGEMENTS MW would like to thank H. Domínguez Sanchez and M. Huertas-Company for helpful discussions. MW acknowledges funding from the Science and Technology Funding Council (STFC) Grant Code ST/R505006/1. We also acknowledge support from STFC under grant ST/N003179/1. LF, CS, HD, and DW acknowledge partial support from one or more of the US National Science Foundation grants IIS-1619177, OAC-1835530, and AST-1716602. This research made use of the open-source python scientific computing ecosystem, including scipy (Jones et al. 2001 ), matplotlib (Hunter 2007 ), scikit-learn (Pedregosa et al. 2011 ), scikit-image (van der Walt et al. 2014 ), and pandas (McKinney 2010 ). This research made use of astropy , a community-developed core python package for Astronomy (The Astropy Collaboration 2013 , 2018 ). This research made use of TensorFlow (Abadi et al. 2015 ). All code is publicly available on GitHub at www.github.com/mwalmsley/galaxy-zoo-bayesian-cnn (Walmsley 2019 ).