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Large spectroscopic surveys have measured atmospheric parameters for millions of Milky Way stars, but differences in instruments, wavelength ranges, analysis methods, and assumptions introduce survey-dependent systematics that complicate their joint use. We aim to place effective temperature, surface gravity, and metallicity estimates from major spectroscopic surveys onto a common, externally validated scale, and to provide a homogenised catalogue for large-scale Galactic studies. We construct the calibration hierarchically. We first define an internal reference scale from the best-populated and best-overlapped surveys (APOGEE, GALAH, and LAMOST LRS), and model survey-to-reference corrections and their uncertainties with machine-learning regression. The scale is then extended to LAMOST MRS, Gaia RVS, RAVE, DESI, Gaia-ESO, and SEGUE, and anchored to high-quality measurements from the PASTEL database. The calibration reduces survey-to-survey offsets and improves consistency in independent overlap samples: independent calibration of GALAH and LAMOST LRS temperatures onto the APOGEE scale reduces their median offset from 44.5 K to 6.2 K. The final catalogue contains about 10.13 million stars, including 6.10 million in the recommended high-quality subset and 3.69 million in the metallicity-optimised subset. For the high-quality subset, Gaia benchmark stars give median residuals of 30 K in Teff, 0.03 dex in log g, and $-0.02$ dex in [Fe/H]. The [Fe/H]-optimised subset gives median residuals of 0.003 dex against Gaia benchmark stars, 0.05 dex for globular clusters, and $-0.02$ dex for open clusters. As an example application, we confirm the presence of metal-poor stars on thin-disc-like orbits, including stars with [Fe/H] $< -2$, showing that the catalogue can be used to study rare Galactic populations on a consistent multi-survey scale.
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Avdeeva et al. (2026) studied this question.
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