LEDA 3445254 , the SIMBAD biblio

LEDA 3445254 , the SIMBAD biblio (20 results) C.D.S. - SIMBAD4 rel 1.8 - 2026.10.14CEST22:55:13

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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
2008A&A...487...33B viz 15       D               324 12 Optical analysis of the poor clusters Abell 610, Abell 725, and Abell 796, containing diffuse radio sources. BOSCHIN W., BARRENA R., GIRARDI M., et al.
2011AJ....142..170H viz 15       D               1 15886 568 The Arecibo Legacy Fast ALFA survey: the α.40 H I source catalog, its characteristics and their impact on the derivation of the H I mass function. HAYNES M.P., GIOVANELLI R., MARTIN A.M., et al.
2014ApJ...788...45T viz 15       D               1 224166 54 Luminosity and redshift dependence of the covering factor of active galactic nuclei viewed with WISE and Sloan Digital Sky Survey. TOBA Y., OYABU S., MATSUHARA H., et al.
2015ApJ...809..146B viz 16       D               1 1719 72 A study in blue: the baryon content of isolated low-mass galaxies. BRADFORD J.D., GEHA M.C. and BLANTON M.R.
2016A&A...593A..40V viz 16       D               1 2182 2 Full stellar kinematical profiles of central parts of nearby galaxies. VUDRAGOVIC A., SAMUROVIC S. and JOVANOVIC M.
2017A&A...599A..71D viz 16       D               1 209271 41 Aperture-free star formation rate of SDSS star-forming galaxies. DUARTE PUERTAS S., VILCHEZ J.M., IGLESIAS-PARAMO J., et al.
2017AJ....154...86W viz 16       D               2 4614 272 The SDSS-IV MaNGA sample: design, optimization, and usage considerations. WAKE D.A., BUNDY K., DIAMOND-STANIC A.M., et al.
2018ApJ...861...49H viz 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.
2019MNRAS.483.2057F viz 16       D               1 4600 64 SDSS-IV MaNGA PyMorph Photometric and Deep Learning Morphological Catalogues and implications for bulge properties and stellar angular momentum. FISCHER J.-L., DOMINGUEZ SANCHEZ H. and BERNARDI M.
2020ApJ...896..121L 16       D               1 92 ~ Wolf-Rayet galaxies in SDSS-IV MaNGA. I. Catalog construction and sample properties. LIANG F.-H., LI C., LI N., et al.
2021ApJ...908..165P viz 17       D               1 631 ~ SDSS-IV/MaNGA: can impulsive gaseous inflows explain steep oxygen abundance profiles and anomalously low-metallicity regions? PACE Z.J., TREMONTI C., SCHAEFER A.L., et al.
2022MNRAS.509.3966W viz 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.
2022MNRAS.513..389R viz 17       D               1 1816 8 Star-forming S0 Galaxies in SDSS-MaNGA: fading spirals or rejuvenated S0s? RATHORE H., KUMAR K., MISHRA P.K., et al.
2022ApJS..261...21Y viz 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 viz 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.
2022A&A...666A.186D viz 17       D               1 194359 6 Mass-metallicity and star formation rate in galaxies: A complex relation tuned to stellar age. DUARTE PUERTAS S., VILCHEZ J.M., IGLESIAS-PARAMO J., et al.
2023A&A...674A..85A viz 17       D               1 6495 2 Classifying the full SDSS-IV MaNGA Survey using optical diagnostic diagrams: Presentation of AGN catalogs in flexible apertures. ALBAN M. and WYLEZALEK D.
2023ApJS..269....3M viz 17       D               1 356397 ~ Siena Galaxy Atlas 2020. MOUSTAKAS J., LANG D., DEY A., et al.
2024ApJ...970...83B 18       D               1 2480 ~ Structure and Kinematics of Star-forming Elliptical Galaxies in SDSS-MaNGA. BISWAS P. and WADADEKAR Y.
2024NatAs...8.1310A viz 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.

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