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| [SHM2017] J010.39368+24.59176 , the SIMBAD biblio (4 results) | C.D.S. - SIMBAD4 rel 1.8 - 2024.04.16CEST09:12:38 |
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More on score
| Bibcode/DOI | Score |
in Title|Abstract| Keywords |
in a table | in teXt, Caption, ... | Nb occurence | Nb objects in ref |
Citations (from ADS) |
Title | First 3 Authors |
|---|---|---|---|---|---|---|---|---|---|
2017AJ....153..204S 
|
16 | D | 1 | 46977 | 123 | Machine-learned identification of RR Lyrae stars from sparse, multi-band data: the PS1 sample. | SESAR B., HERNITSCHEK N., MITROVIC S., et al. | ||
|
2018AJ....156..241H
|
16 | D | 1 | 311114 | 199 | A first catalog of variable stars measured by the Asteroid Terrestrial-impact Last Alert System (ATLAS). | HEINZE A.N., TONRY J.L., DENNEAU L., et al. | ||
|
2019A&A...622A..60C
|
17 | D | 1 | 150347 | 194 | Gaia Data Release 2. Specific characterisation and validation of all-sky Cepheids and RR Lyrae stars. | CLEMENTINI G., RIPEPI V., MOLINARO R., et al. | ||
|
2022ApJS..261...33D
|
18 | D | 1 | 104673 | 3 | Photometric Metallicity Prediction of Fundamental-mode RR Lyrae Stars in the Gaia Optical and Ks Infrared Wave Bands by Deep Learning. | DEKANY I. and GREBEL E.K. |
