Learning on knowledge graph dynamics provides an early warning of impactful research

The scientific ecosystem relies on citation-based metrics that provide only imperfect, inconsistent and easily manipulated measures of research quality. Here we describe DELPHI (Dynamic Early-warning by Learning to Predict High Impact), a framework that provides an early-warning signal for ‘impactfu...

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Veröffentlicht in:	Nature biotechnology Jg. 39; H. 10; S. 1300 - 1307
Hauptverfasser:	Weis, James W., Jacobson, Joseph M.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Nature Publishing Group US 01.10.2021 Nature Publishing Group
Schlagworte:	631/114/1305 631/114/2406 706/648/1496 Agriculture Analysis Artificial intelligence Bibliometrics Bioinformatics Biomedical and Life Sciences Biomedical Engineering/Biotechnology Biomedicine Biotechnology Datasets Funding Graph theory Knowledge representation Learning algorithms Life Sciences Machine learning Mathematical analysis Scientific papers Warning systems United States
ISSN:	1087-0156, 1546-1696, 1546-1696
Online-Zugang:	Volltext
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