TYC 3142-70-1 , the SIMBAD biblio

TYC 3142-70-1 , the SIMBAD biblio (10 results) C.D.S. - SIMBAD4 rel 1.8 - 2024.04.19CEST15:34:47

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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
2013A&A...557L..10N viz 16       D               1 12151 189 Rotation periods of 12000 main-sequence Kepler stars: dependence on stellar spectral type and comparison with v sin i observations. NIELSEN M.B., GIZON L., SCHUNKER H., et al.
2014AJ....148..125P 94       D       C       2 75 3 The EB Factory project. II. Validation with the Kepler field in preparation for K2 and TESS. PARVIZI M., PAEGERT M. and STASSUN K.G.
2015MNRAS.449.1401H viz 16       D               1 3011 6 A large sample of metallic-line star candidates from LAMOST Data Release 1. HOU W., LUO A., YANG H., et al.
2016AJ....151...68K viz 16       D               1 2914 316 Kepler eclipsing binary stars. VII. The catalog of eclipsing binaries found in the entire Kepler data set. KIRK B., CONROY K., PRSA A., et al.
2016A&A...594A..39F viz 16       D               1 51408 86 Activity indicators and stellar parameters of the Kepler targets. An application of the ROTFIT pipeline to LAMOST-Kepler stellar spectra. FRASCA A., MOLENDA-ZAKOWICZ J., DE CAT P., et al.
2016AJ....152..158T viz 16       D               1 4387 37 Detection of potential transit signals in 17 quarters of Kepler data: results of the final Kepler mission transiting planet search (DR25). TWICKEN J.D., JENKINS J.M., SEADER S.E., et al.
2017AJ....154..250L viz 16       D               1 2280 72 Tidal synchronization and differential rotation of Kepler eclipsing binaries. LURIE J.C., VYHMEISTER K., HAWLEY S.L., et al.
2019ApJS..244...43Z viz 17       D               1 1328 22 Unbiased distribution of binary parameters from LAMOST and Kepler observations. ZHANG J., QIAN S.-B., WU Y., et al.
2020ApJS..251...15Z viz 17       D               1 20896 38 Phase II of the LAMOST-Kepler/K2 survey. I. Time series of medium-resolution Spectroscopic observations. ZONG W., FU J.-N., DE CAT P., et al.
2022ApJS..259...63S viz 18       D               1 10264 2 Objective Separation between CP1 and CP2 Based on Feature Extraction with Machine Learning. SHANG L.-H., LUO A.-L., WANG L., et al.

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