  Gaia Data Release 3 will contain more than a billion sources with positions,
parallaxes, and proper motions. In addition, for hundreds of millions of stars,
it will include low-resolution blue photometer (BP) and red photometer (RP)
spectra. Obtained by dispersing light with prisms, these spectra have
resolutions that are too low to allow us to measure individual spectral lines
and bands. However, the combined BP/RP spectra can be used to estimate some
stellar properties such as $T_{\text{eff}}$, $\log{g}$, and $\left[ \text{M} /
\text{H} \right]$.
  We investigate the feasibility of using the ExtraTrees algorithm to estimate
the alpha element to iron abundance ratio $\left[ \alpha / \text{H} \right]$
from low-resolution BP/RP spectra.
  To infer $\left[ \alpha / \text{H} \right]$ from the spectra, we created
regression models trained on two samples: a set of synthetic spectra and a set
of observed spectra from stars that have known $\left[ \alpha / \text{H}
\right]$ since they have been observed using HERMES. We applied each model to
the other sample and to a larger observed sample to assess the performance of
the models. In addition, we used our models to analyse stars from the
Gaia-Enceladus structure.
  We find that models using the ExtraTrees algorithm can be used to estimate
$\left[ \alpha / \text{H} \right]$ from low-resolution BP/RP spectra of cool
stars. However, they do this by exploiting correlations between $\left[ \alpha
/ \text{H} \right]$ and other parameters, rather than the causal effect of
$\left[ \alpha / \text{H} \right]$ on the spectrum. Hence, they are unlikely to
be useful in studies that attempt to distinguish stars that only differ in
$\left[ \alpha / \text{H} \right]$.
