This paper is a review of the following cited work
Csefalvay, Chris von (June 13, 2021). "Early evidence for the safety of certain COVID-19 vaccines using empirical Bayesian modeling from VAERS". medRxiv: 2021.06.10.21258589. doi:10.1101/2021.06.10.21258589. ISSN 2125-8589. S2CID 235413778.
It is, as of time of publishing, being used as a citation on the Vacine Adverse Event Reporting System article on Wikipedia which has the following text (highlight is where citation is found):
During the COVID-19 pandemic, raw VAERS data has often been disseminated by anti-vaccine groups in order to justify misinformation and safety claims related to COVID-19 vaccines, including adverse reactions and alleged fatalities claimed to have been caused by vaccines.Websites such as Medalerts (published by the anti-vaccine group National Vaccine Information Center) and OpenVAERS (which published a tally of vaccine adverse events and fatalities allegedly linked to COVID-19 vaccines based on VAERS data), have been linked to this misinformation. Comparative studies of VAERS, which look at relative reporting rates, have found that the data does not support these claims. ______________
The paper uses an algorithm to get a value (data-set from beginning of data to 28 May 2021, beginning of data I assume to be December 20, 2020) to produce a metric called EBGM.