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| V* V795 Cep , the SIMBAD biblio (10 results) | C.D.S. - SIMBAD4 rel 1.8 - 2026.10.17CEST04:59:26 |
| 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 |
|---|---|---|---|---|---|---|---|---|---|
| 2007OEJV...59....1O | 15 | 0 | New and confirmed RR Lyrae variables found in the NSVS and ASAS-3 databases. | OTERO S. | |||||
|
2011IBVS.5969....1K |
15 | D | 1 | 2041 | 27 | The 80th name-list of variable stars. Part I - RA 0h to 6h. | KAZAROVETS E.V., SAMUS N.N., DURLEVICH O.V., et al. | ||
|
2014MNRAS.441..715G |
15 | D | 1 | 13086 | 14 | A mid-infrared study of RR Lyrae stars with the Wide-field Infrared Survey Explorer all-sky data release. | GAVRILCHENKO T., KLEIN C.R., BLOOM J.S., et al. | ||
|
2017A&A...605A..79G |
16 | D | 1 | 735 | 92 | Gaia Data Release 1. Testing parallaxes with local Cepheids and RR Lyrae stars. | GAIA COLLABORATION, CLEMENTINI G., EYER L., et al. | ||
|
2019ApJ...879...69T |
16 | D | 1 | 222610 | 141 | The Payne: self-consistent ab initio fitting of stellar spectra. | TING Y.-S., CONROY C., RIX H.-W., et al. | ||
|
2020ApJS..247...68L |
16 | D | 1 | 6244 | 20 | Probing the Galactic halo with RR Lyrae stars. I. The catalog. | LIU G.-C., HUANG Y., ZHANG H.-W., et al. | ||
|
2020AJ....160..120J |
16 | D | 1 | 365763 | 238 | APOGEE data and spectral analysis from SDSS Data Release 16: seven years of observations including first results from APOGEE-South. | JONSSON H., HOLTZMAN J.A., ALLENDE PRIETO C., et al. | ||
|
2022AJ....163..152S |
17 | D | 1 | 583193 | 11 | APOGEE Net: An Expanded Spectral Model of Both Low-mass and High-mass Stars. | SPRAGUE D., CULHANE C., KOUNKEL M., et al. | ||
|
2022ApJS..259...35A |
17 | D | 1 | 611005 | 320 | The Seventeenth Data Release of the Sloan Digital Sky Surveys: Complete Release of MaNGA, MaStar, and APOGEE-2 Data. | ABDURRO'UF, ACCETTA K., AERTS C., et al. | ||
|
2024AJ....167..192D |
18 | D | 1 | 1374 | ~ | Detection of Contact Binary Candidates Observed By TESS Using the Autoencoder Neural Network. | DING X., SONG Z., WANG C., et al. |