The problem is that GZ relies on a user base that wants to look at the interesting objects - this will look at all the boring stuff too. Plus, data rates of LSST will be 10s TB/night - this will have to be parsed extremely quickly to find transients. Can't envision crowd sourcing doing that.
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Fair enough, but this is truly unsupervised learning, which has not properly been applied to astro-images before
No, this is quite distinct from astrometry.net (assume that's what you mean)
The problem is that GZ relies on a user base that wants to look at the interesting objects - this will look at all the boring stuff too. Plus, data rates of LSST will be 10s TB/night - this will have to be parsed extremely quickly to find transients. Can't envision crowd sourcing doing that.