ML regressors trained on APOGEE DR17 red giants predict C, O, Mg, Si abundances from kinematics and [Fe/H] more accurately than [Fe/H] baseline, with external validation on HARPS FGK dwarfs and reproduction of Galactic chemical evolution trends.
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Inferring stellar metallicity and elemental abundances from kinematic and spectroscopic data using machine learning -- Implications for exoplanet host stars
ML regressors trained on APOGEE DR17 red giants predict C, O, Mg, Si abundances from kinematics and [Fe/H] more accurately than [Fe/H] baseline, with external validation on HARPS FGK dwarfs and reproduction of Galactic chemical evolution trends.