VizieR Online Data Catalog: Lithium with Machine-Learning (Nepal+, 2023)

This catalog includes atmospheric parameters and lithium abundances, along with their uncertainties, for 40150 GIRAFFE HR15N spectra, parametrized using Convolutional Neural Networks. The catalog also contains, the spectra name and GES identifier, the signal-to-noise ratio of the spectra and flags indicating which labels are within the training set limits. The training data for this machine learning application were obtained from the Gaia-ESO survey. The accompanying paper describes the training data, the CNN method, and presents extensive validation using benchmarks and external catalogs, as well as two science applications of the catalog.

(1 data file).