  Doctoral theses are an important source of publication in universities,
although little research has been carried out on the publications resulting
from theses, on so-called derivative articles. This study investigates how
derivative articles can be identified through a text analysis based on the
full-text of a set of medical theses and the full-text of articles, with which
they shared authorship. The text similarity analysis methodology applied
consisted in exploiting the full-text articles according to organization of
scientific discourse (IMRaD) using the TurnItIn plagiarism tool. The study
found that the text similarity rate in the Discussion section can be used to
discriminate derivative articles from non-derivative articles. Additional
findings were: the first position of the thesis's author dominated in 85% of
derivative articles, the participation of supervisors as coauthors occurred in
100% of derivative articles, the authorship credit retained by the thesis's
author was 42% in derivative articles, the number of coauthors by article was 5
in derivative articles versus 6.4 coauthors, as average, in non-derivative
articles and the time differential regarding the year of thesis completion
showed that 87.5% of derivative articles were published before or in the same
year of thesis completion.
