KOI-3816 , the SIMBAD biblio

KOI-3816 , the SIMBAD biblio (10 results) C.D.S. - SIMBAD4 rel 1.8 - 2026.10.16CEST20:53:01

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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
2012ApJS..199...24T viz 15       D               1 5394 66 Detection of potential transit signals in the first three quarters of Kepler mission data. TENENBAUM P., CHRISTIANSEN J.L., JENKINS J.M., et al.
2012ApJ...754..129S 15       D               1 90 31 Planet hunters: assessing the Kepler inventory of short-period planets. SCHWAMB M.E., LINTOTT C.J., FISCHER D.A., et al.
2014AJ....147..119C viz 15       D               2 8013 91 Contamination in the Kepler field. Identification of 685 KOIs as false positives via ephemeris matching based on Q1-Q12 data. COUGHLIN J.L., THOMPSON S.E., BRYSON S.T., et al.
2015ApJS..217...16R viz 16       D               1 8625 149 Planetary candidates observed by Kepler. V. Planet sample from Q1-Q12 (36 months). ROWE J.F., COUGHLIN J.L., ANTOCI V., et al.
2016ApJ...822...86M viz 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.
2017MNRAS.465.2634A viz 16       D               1 5400 21 Transit shapes and self-organizing maps as a tool for ranking planetary candidates: application to Kepler and K2. ARMSTRONG D.J., POLLACCO D. and SANTERNE A.
2017MNRAS.469.4578H viz 16       D               1 8666 48 Deep learning classification in asteroseismology. HON M., STELLO D. and YU J.
2018MNRAS.476.3233H viz 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 viz 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.
2021MNRAS.504.5327A 17       D               1 7000 19 Exoplanet validation with machine learning: 50 new validated Kepler planets. ARMSTRONG D.J., GAMPER J. and DAMOULAS T.

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