activity
20192022
most citedThe Gaia-ESO Survey: Probing the lithium abundances in old metal-rich dwarf stars in the Solar vicinity

9 citations · 12 across the 4 of their papers we have counts for

collaborators

8 papers

astro-ph.SR20229 cited

The Gaia-ESO Survey: Probing the lithium abundances in old metal-rich dwarf stars in the Solar vicinity

M. L. L. Dantas, G. Guiglion, R. Smiljanic +14

We test a scenario in which radial migration could affect the Li abundance pattern of dwarf stars in the solar neighbourhood. This may confirm that the Li abundance in these stars…

astro-ph.GA2021

The Fornax Cluster through S-PLUS

A. V. Smith Castelli, C. Mendes de Oliveira, F. Herpich +25

The Southern Photometric Local Universe Survey (S-PLUS) aims to map 9300 deg of the Southern sky using the Javalambre filter system of 12 optical bands, 5 Sloan-like…

physics.soc-ph2020

Women in academia: a warning on selection bias in gender studies from the astronomical perspective

M. L. L. Dantas, E. Cameron, Rafael S. de Souza +13

The recent paper by AlShebli et al. (2020) investigates the impact of mentorship in young scientists. Among their conclusions, they state that female protégés benefit more from mal…

astro-ph.GA2020

UV upturn versus UV weak galaxies: differences and similarities of their stellar populations unveiled by a de-biased sample

M. L. L. Dantas, P. R. T. Coelho, P. Sánchez-Blázquez

The ultraviolet (UV) upturn is characterised by an unexpected up-rise of the UV flux in quiescent galaxies between the Lyman limit and 2500Å. By making use of colour-colour diagram…

astro-ph.GA20203 cited

AGN dichotomy beyond radio loudness: a Gaussian Mixture Model analysis

Pedro P. B. Beaklini, Allan V. C. Quadros, Marcio G. B. de Avellar +2

Since the discovery of Quasi-stellar Objects (QSOs), also known as quasars, they have been traditionally subdivided as radio-loud and radio-quiet sources. Whether such division is…

astro-ph.GA2019

The S-PLUS: a star/galaxy classification based on a Machine Learning approach

M. V. Costa-Duarte, L. Sampedro, A. Molino +32

We present a star/galaxy classification for the Southern Photometric Local Universe Survey (S-PLUS), based on a Machine Learning approach: the Random Forest algorithm. We train the…