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2) In GZH, the galaxies chosen to be FERENGI'd were from SDSS; so the pixel scale needed to be adjusted to match HST. This created a problem for the galaxies at the lowest redshifts, because these images couldn't be redshifted all the way to z = 1.0; so effectively these galaxies provided no useful data. Is there any reason not to start with Hubble galaxies at low z instead, to avoid this problem?     3) Evolution correction - Images were created with a number of assumed evolutions - I'm not sure this was well thought-out, and we should discuss how we could implement this most effectively to the new data.   4) Because of the way the decision tree is structured, we did not have nearly enough answers to higher-order questions beyond 'smooth or features,' so we couldn't use FERENGI to measure redshift bias of users at all. Huge waste. We can improve on this once the new filtering method is implemented - my ensuring potential bars, spirals, clumps, etc are actually seen by users, even if the smoothness of the image would've previously prevented them from ever seeing the question, we can make sure we have enough data to debias *all* questions!  \subsubsection{Illustris}  Illustris provides snapshots of galaxies at a wide range of redshifts, so these could also be used to quantify user bias. The advantage here is that we do not need to bin these in redshift bins - we could more easily fit a continuous function of vote fractions vs redshift, as there are ~60 snapshots of galaxies available between $0