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Precise distances, masses, ages and 3D velocities of ~140000 red clump stars

<p>We present a sample of $\sim$\,140,000 primary red clump (RC) stars of spectral signal-to-noise ratios higher than 20 from the LAMOST Galactic spectroscopic surveys, selected based on their positions in the metallicity-dependent effective temperature--surface gravity and color--metallicity diagrams, supervised by high-quality $Kepler$ asteroseismology data.<br> The stellar masses and ages of those stars are further determined from the LAMOST spectra, using the Kernel Principal Component Analysis method, trained with thousands of RCs in the&nbsp; LAMOST-$Kepler$ fields with accurate asteroseismic mass measurements. &nbsp;<br> The purity and completeness of our primary RC sample are generally higher than 80\,per cent.<br> For the mass and age, a variety of tests show typical uncertainties of 15 and 30\,per cent, respectively.<br> Using over ten thousand primary RCs with accurate distance measurements from the parallaxes of Gaia\,DR2, we re-calibrate the $K_{\rm s}$ absolute magnitudes of primary RCs by, for the first time, considering both the metallicity and age dependencies.<br> With the the new calibration, distances are derived for all the primary RCs, with a typical uncertainty of 5--10\,per cent,&nbsp; even better than the values yielded by the Gaia parallax measurements for stars beyond 3--4\,kpc.<br> The sample covers a significant volume of the Galactic disk of $4\,\leq\,R\,\leq\,16$\,kpc, $|Z|\,\leq\,5$\,kpc, and $-20\,\leq\,\phi\,\leq\,50^{\circ}$.<br> Stellar atmospheric parameters, line-of-sight velocities and elemental abundances derived from the LAMOST spectra and proper motions of Gaia\,DR2 are also provided for the sample stars.<br> Finally, the selection function of the sample is carefully evaluated in the color-magnitude plane for different sky areas.</p> <p>Details about the table:</p> <p>&nbsp; RA: Right ascension (degrees)<br> &nbsp; DEC: Declination (degrees)<br> &nbsp; GLON: Galactic longitude l (degrees)<br> &nbsp; GLAT: Galactic latitude b (degrees)<br> &nbsp; RV: Line-of-sight velocity (km/s)<br> &nbsp; ERR_RV: Uncertainty of line-of-sight velocity (km/s)<br> &nbsp; TEFF: Effective temperature (K)<br> &nbsp; ERR_TEFF: Uncertainty of effective temperature (K)<br> &nbsp;&nbsp; LOGG: Surface gravity<br> &nbsp;&nbsp; ERR_LOGG: Uncertainty of surface gravity<br> &nbsp;&nbsp; FEH: Metallicity<br> &nbsp;&nbsp; ERR_FEH: Uncertainty of metallicity<br> &nbsp;&nbsp; AFE: Alpha-to-iron abundance<br> &nbsp;&nbsp; ERR_AFE: Uncertainty of apha-to-iron abundance<br> &nbsp;&nbsp; AGE: Stellar age (Gyr)<br> &nbsp;&nbsp; ERR_AGE: Uncertainty of stellar age (Gyr)<br> &nbsp;&nbsp; MASS: Stellar mass (solar mass)<br> &nbsp;&nbsp; ERR_MASS: Uncertainty of stellar mass (solar mass)<br> &nbsp;&nbsp; J: 2MASS J band magnitude<br> &nbsp;&nbsp; ERR_J: Uncertainty of 2MASS J band magnitude<br> &nbsp;&nbsp; H: 2MASS H band magnitude<br> &nbsp;&nbsp; ERR_H: Uncertainty of 2MASS H band magnitude<br> &nbsp;&nbsp; KS: 2MASS Ks band magnitude<br> &nbsp;&nbsp; ERR_KS: Uncertainty of 2MASS Ks band magnitude<br> &nbsp;&nbsp; G: Gaia DR2 G band magnitude<br> &nbsp;&nbsp; ERR_G: Uncertainty of Gaia DR2 G band magnitude<br> &nbsp;&nbsp; BP: Gaia DR2 BP band magnitude<br> &nbsp;&nbsp; ERR_BP: Uncertainty of Gaia DR2 BP band magnitude<br> &nbsp;&nbsp; RP: Gaia DR2 RP band magnitude<br> &nbsp;&nbsp; ERR_RP: Uncertainty of Gaia DR2 RP band magnitude<br> &nbsp;&nbsp; EBV: E (B - V) (mag)<br> &nbsp;&nbsp; MKS: Absolute magnitude in Ks band<br> &nbsp;&nbsp; DISTANCE: distance (kpc)<br> &nbsp;&nbsp; ERR_DISTANCE: Uncertainty of distance (kpc)<br> &nbsp;&nbsp; PARALLAX: Gaia DR2 parallax (mas)<br> &nbsp;&nbsp; ERR_PARALLAX: Uncertainty of Gaia DR2 parallax (mas)<br> &nbsp;&nbsp; PMRA: Proper motion in R.A. (mas/yr)<br> &nbsp;&nbsp; ERR_PMRA: Uncertainty of proper motion in R.A. (mas/yr)<br> &nbsp;&nbsp; PMDEC: Proper motion in Dec. (mas/yr)<br> &nbsp;&nbsp; ERR_PMDEC: Uncertainty of proper motion in Dec. (mas/yr)<br> &nbsp;&nbsp; F_CMD: Selection fraction in color-magnitude diagram</p>

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28/100

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These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
4
Access
16
Reuse readiness
0
Engagement
4