other query modes : |
Identifier query |
Coordinate query |
Criteria query |
Reference query |
Basic query |
Script submission |
TAP |
Output options |
Object types |
Help |
[SHM2017] J029.07305+55.92306 , the SIMBAD biblio (3 results) | C.D.S. - SIMBAD4 rel 1.8 - 2024.05.03CEST00:54:10 |
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. | ||
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. |