Abundance Estimates for 16 Elements in 6 Million Stars from LAMOST DR5
  Low-Resolution Spectra
  We present the determination of stellar parameters and individual elemental
abundances for 6 million stars from $\sim$8 million low-resolution
($R\sim1800$) spectra from LAMOST DR5. This is based on a modeling approach
that we dub $The$ $Data$--$Driven$ $Payne$ ($DD$--$Payne$), which inherits
essential ingredients from both {\it The Payne} \citep{Ting2019} and $The$
$Cannon$ \citep{Ness2015}. It is a data-driven model that incorporates
constraints from theoretical spectral models to ensure the derived abundance
estimates are physically sensible. Stars in LAMOST DR5 that are in common with
either GALAH DR2 or APOGEE DR14 are used to train a model that delivers stellar
parameters ($T_{\rm eff}$, $\log g$, $V_{\rm mic}$) and abundances for 16
elements (C, N, O, Na, Mg, Al, Si, Ca, Ti, Cr, Mn, Fe, Co, Ni, Cu, and Ba) when
applied to LAMOST spectra. Cross-validation and repeat observations suggest
that, for ${\rm S/N}_{\rm pix}\ge 50$, the typical internal abundance precision
is 0.03--0.1\,dex for the majority of these elements, with 0.2--0.3\,dex for Cu
and Ba, and the internal precision of $T_{\rm eff}$ and $\log g$ is better than
30\,K and 0.07\,dex, respectively. Abundance systematics at the $\sim$0.1\,dex
level are present in these estimates, but are inherited from the
high-resolution surveys' training labels. For some elements, GALAH provides
more robust training labels, for others, APOGEE. We provide flags to guide the
quality of the label determination and to identify binary/multiple stars in
LAMOST DR5. The abundance catalogs are publicly accessible via
\href{url}{http://dr5.lamost.org/doc/vac}.
