One of the missions of RR\ID is to accelerate peer review of infectious disease research across a wide range of disciplines and deliver almost-real-time, dependable scientific information that policymakers, scholars, and health leaders can use. We do this by soliciting rapid peer reviews of time-sensitive and interesting preprints, which are then published online and linked to the preprint servers that host the manuscripts. RR\ID trains and engages a robust graduate student network to identify—with the support of AI—credible, experienced peer reviewers for each manuscript. The reviewers we select are the same colleagues (i.e., of same/similar subject matter expertise, seniority and experience) as reviewers one would expect from a high-impact scientific journal.
We offer a new take on traditional peer review. RR\ID is trying to balance the need for rigor with the need for rapid responses. Of reviewers, the time for each review will vary based on the preprint and the reviewer. The general question we are asking reviewers is whether a preprint is reliable and trustworthy. Should the preprint be taken seriously or not? Are the findings strong and reliable? If not, and if the preprint is not informative or even misleading, what are the implications? How might the range of evidence and ideas presented or asserted by the main claims of each preprint—whether good, bad, or neither—be used to further our knowledge in fighting the pandemics and other emerging global infections?
We do expect that each manuscript is read carefully and critiqued on it’s strength of evidence. By participating, reviewers will support an innovative research review model created in response to the dire need within the research community to accelerate peer review for the daily influx of COVID-19-related preprints from around the world, across many disciplines. RR:C19 uses machine learning and a network of scholars to identify important preprints that are posted across pre-print servers such as medRxiv, bioRxiv, SSRN, and other repositories of articles that have yet to be peer-reviewed.
An underlying value of RR\ID is transparency and reliability. Each review will be published online and assigned a DOI, making the work fully citable and claimable on reviewers’ ORCID and Publons accounts. Our standard practice is to publish the reviewers’ full names and affiliations, although we will allow reviewers to publish their review anonymously, upon request.
Given our desire to rapidly turn-around preprints, especially those that are already being referenced in the media or by the scientific community, we hope to have reviewers let us know if they’re available to review as soon as possible. We would like for the rapid review to be completed within a month, ideally when there are at least two peer reviews. We encourage reviewers to work with a colleague, graduate student, or post doc (with appropriate credit) to help prepare the review, if desired. We do our best to avoid inviting reviewers with likely conflicts of interest with the authors but also ask all reviewers to notify us of any potential conflicts of interest.
We are working actively with our editorial board, our reviewers, peer-review academic experts and the MIT Press in improving the rigor, speed and reviewer experience of our peer-review process. We are exploring how we can provide information from our screeners to the reviewers; how we might link reviewers to journalists writing about new findings; and how we might incorporate audio and video into the peer review process and any subsequent scientific debates about the reported findings.
Whether contributing to this effort as a screener, peer-reviewer, or adviser, we aim to help build solid, peer-reviewed scientific knowledge about the coronavirus and stem the proliferation of unverified research, which can be misused, misinterpreted, and acted upon in ways that could be (and have been) dangerous for our global community.