A LAMOST BHB Catalog and Kinematics Therein I: Catalog and Halo
  Properties
  We collect a sample of stars observed both in LAMOST and Gaia which have
colors implying a temperature hotter than 7000 K. We train a machine learning
algorithm on LAMOST spectroscopic data which has been tagged with stellar
classifications and metallicities, and use this machine to construct a catalog
of Blue Horizontal Branch stars (BHBs) with metallicity information. Another
machine is trained using Gaia parallaxes to predict absolute magnitudes for
these stars. The final catalog of 13,693 BHBs is thought to be about 86\% pure,
with $\sigma_{[Fe/H]}\sim$0.35 dex and $\sigma_{G}\sim$0.31 mag. These values
are confirmed via comparison to globular clusters, although a covariance error
seems to affect our magnitude and abundance estimates.
  We analyze a subset of this catalog in the Galactic Halo. We find that BHB
populations in the outer halo appear redder, which could imply a younger
population, and that the metallicity gradient is relatively flat around [Fe/H]
= -1.9 dex over our sample footprint. We find that our metal rich BHB stars are
on more radial velocity dispersion dominated orbits ($\beta \sim 0.70$) at all
radii than our metal poor BHB stars ($\beta \sim 0.62$).
