  Large surveys are providing a diversity of spectroscopic observations with
Gaia alone set to deliver millions of Ca-triplet-region spectra across the
Galaxy. We aim to understand the dimensionality of the chemical abundance
information in the Gaia-RVS data to inform galactic archaeology pursuits. We
fit a quadratic model of four primary sources of variability, described by
labels of $T_{\rm eff}$, $\log g$, [Fe/H], and [$\alpha$/Fe], to the normalized
flux of 10,802 red-clump stars from the Gaia-RVS-like ARGOS survey. We examine
the residuals between ARGOS spectra and the models and find that the models
capture the flux variability across $85\%$ of the wavelength region. The
remaining residual variance is concentrated to the Ca-triplet features, at an
amplitude up to $12\%$ of the normalized flux. We use principal component
analysis on the residuals and find orthogonal correlations in the Ca-triplet
core and wings. This variability, not captured by our model, presumably marks
departures from the completeness of the 1D-LTE label description. To test the
indication of low-dimensionality, we turn to abundance-space to infer how well
we can predict measured [Si/H], [O/H], [Ca/H], [Ni/H], and [Al/H] abundances
from the Gaia-RVS-like RAVE survey with models of $T_{\rm eff}$, $\log g$,
[Fe/H], and [Mg/Fe]. We find that we can near-entirely predict these
abundances. Using high-precision APOGEE abundances, we determine that a
measurement uncertainty of $<$ 0.03 dex is required to capture additional
information from these elements. This indicates that a four-label model
sufficiently describes chemical abundance variance for $\approx$ S/N $<$ 200
per pixel, in Gaia-RVS spectra.
