Search

Your search keyword '"Mordaunt, Milo"' showing total 5 results
Start Over Author "Mordaunt, Milo"
5 results on '"Mordaunt, Milo"'

1. Title detection: a novel approach to automatically finding retractions and other editorial notices in the scholarly literature

Author

Uppala, Ashish, Rosati, Domenic, Nicholson, Josh M., Mordaunt, Milo, Grabitz, Peter, and Rife, Sean C.

Subjects
Computer Science - Digital Libraries
Abstract

Despite being a key element in the process of disseminating scientific knowledge, editorial notices are often obscured and not clearly linked to the papers to which they refer. In the present paper, we describe established methods of aggregating notice data, and introduce a novel method of finding editorial notices in the scientific literature. Specifically, we describe how article titles denote notices to existing publications, and how this information can be used to tie notices to papers in an automated fashion. Finally, as part of a broader movement to make science more transparent, we make notices detected through this and other methods publicly available and describe this dataset and how it can be accessed.

Published
2022

5. Measuring the quality of scientific references in Wikipedia: an analysis of more than 115M citations to over 800 000 scientific articles.

Author

Nicholson, Joshua M., Uppala, Ashish, Sieber, Matthias, Grabitz, Peter, Mordaunt, Milo, and Rife, Sean C.

Subjects
MACHINE learning, PERIODICAL articles
Abstract

Wikipedia is a widely used online reference work which cites hundreds of thousands of scientific articles across its entries. The quality of these citations has not been previously measured, and such measurements have a bearing on the reliability and quality of the scientific portions of this reference work. Using a novel technique, a massive database of qualitatively described citations, and machine learning algorithms, we analyzed 1 923 575 Wikipedia articles which cited a total of 824 298 scientific articles in our database and found that most scientific articles cited by Wikipedia articles are uncited or untested by subsequent studies, and the remainder show a wide variability in contradicting or supporting evidence. Additionally, we analyzed 51 804 643 scientific articles from journals indexed in the Web of Science and found that similarly most were uncited or untested by subsequent studies, while the remainder show a wide variability in contradicting or supporting evidence. [ABSTRACT FROM AUTHOR]

Published
2021
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results