Appendix of the paper entitled "Chasing the formation history of the Galactic metal-poor disk".

For the machine learning reference set, we used stars from Li et al. (2022a) and JINAbase Abohalima & Frebel (2018), Fig. A.1 presents the distribution of stellar parameters for the reference set and target stars. Noting systematic biases between the two sources.

Fig. A.2 compares atmospheric parameters and chemical abundances for stars common to both sources, and Table A.1 lists parameters for revising abundances from JINAbase Abohalima & Frebel (2018), with details in Section 2.1.1. Table A.2 specifies the wavelength ranges used to estimate Fe, Mg, Ca, and C abundances via template fitting. Fig. A.3 shows machine learning accuracy on training and test sets, while Fig. A.4 illustrates the relationship between errors and prediction accuracy.