|
other query modes : |
Identifier query |
Coordinate query |
Criteria query |
Reference query |
Basic query |
Script submission |
TAP |
Output options |
Object types |
Help |
| LEDA 1213354 , the SIMBAD biblio (9 results) | C.D.S. - SIMBAD4 rel 1.8 - 2026.10.14CEST19:38:00 |
| 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 |
|---|---|---|---|---|---|---|---|---|---|
|
2001MNRAS.328.1039C |
206872 | 1908 | The 2dF Galaxy Redshift Survey: spectra and redshifts. | COLLESS M., DALTON G., MADDOX S., et al. | |||||
|
2003A&A...412...45P |
15 | D | 1 | 956189 | 750 | HYPERLEDA. I. Identification and designation of galaxies. | PATUREL G., PETIT C., PRUGNIEL P., et al. | ||
|
2010MNRAS.409.1455H |
15 | D | 1 | 425 | 4 | The stellar populations of early-type galaxies – I. Observations, line strengths and stellar population parameters. | HARRISON C.D., COLLESS M., KUNTSCHNER H., et al. | ||
|
2018ApJ...861...49H |
16 | D | 1 | 31270 | 293 | The Arecibo Legacy Fast ALFA survey: the ALFALFA extragalactic H I source catalog. | HAYNES M.P., GIOVANELLI R., KENT B.R., et al. | ||
|
2020MNRAS.494.2090J |
16 | D | 4 | 5735 | ~ | The H I mass function of group galaxies in the ALFALFA survey. | JONES M.G., HESS K.M., ADAMS E.A.K., et al. | ||
|
2022MNRAS.509.3966W |
17 | D | 1 | 89291 | 61 | Galaxy Zoo DECaLS: Detailed visual morphology measurements from volunteers and deep learning for 314 000 galaxies. | WALMSLEY M., LINTOTT C., GERON T., et al. | ||
|
2022ApJS..261...21Y |
17 | D | 1 | 29963 | 6 | Statistical Analysis of H I Profile Asymmetry and Shape for Nearby Galaxies. | YU N., HO L.C., WANG J., et al. | ||
|
2022ApJS..262...36S |
17 | D | 1 | 10075 | 23 | SDSS-IV MaNGA: pyPipe3D Analysis Release for 10,000 Galaxies. | SANCHEZ S.F., BARRERA-BALLESTEROS J.K., LACERDA E., et al. | ||
|
2024NatAs...8.1310A |
18 | D | 1 | 10075 | ~ | Constraints on the in situ and ex situ stellar masses in nearby galaxies obtained with artificial intelligence. | ANGELOUDI E., FALCON-BARROSO J., HUERTAS-COMPANY M., et al. |