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| KOI-6898 , the SIMBAD biblio (7 results) | C.D.S. - SIMBAD4 rel 1.8 - 2026.10.16CEST09:11:46 |
| 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 |
|---|---|---|---|---|---|---|---|---|---|
|
2016ApJ...822...86M |
16 | D | 1 | 6130 | 337 | False positive probabilities for all Kepler objects of interest: 1284 newly validated planets and 428 likely false positives. | MORTON T.D., BRYSON S.T., COUGHLIN J.L., et al. | ||
|
2017AJ....153...66Z |
16 | D | 1 | 1663 | 45 | Robo-AO Kepler Planetary Candidate Survey. III. Adaptive optics imaging of 1629 Kepler exoplanet candidate host stars. | ZIEGLER C., LAW N.M., MORTON T., et al. | ||
|
2017AJ....153...71F |
16 | D | 1 | 3575 | 164 | The Kepler follow-up observation program. I. A catalog of companions to Kepler stars from high-resolution imaging. | FURLAN E., CIARDI D.R., EVERETT M.E., et al. | ||
|
2016PASP..128g4502M |
16 | D | 1 | 305 | 14 | Identifying false alarms in the Kepler planet candidate catalog. | MULLALLY F., COUGHLIN J.L., THOMPSON S.E., et al. | ||
|
2018MNRAS.476.3233H |
16 | D | 1 | 15009 | 17 | Deep learning classification in asteroseismology using an improved neural network: results on 15 000 Kepler red giants and applications to K2 and TESS data. | HON M., STELLO D. and YU J. | ||
|
2018ApJS..236...42Y |
16 | D | 1 | 16097 | 158 | Asteroseismology of 16,000 Kepler red giants: global oscillation parameters, masses, and radii. | YU J., HUBER D., BEDDING T.R., et al. | ||
|
2022A&A...664A..78F |
17 | D | 1 | 7452 | 7 | Characterization of Kepler targets based on medium-resolution LAMOST spectra analyzed with ROTFIT,. | FRASCA A., MOLENDA-ZAKOWICZ J., ALONSO-SANTIAGO J., et al. |