ScreenIT
The Automated Screening Working Groups is a group of software engineers and biologists passionate about improving scientific manuscripts on a large scale. Our members have created tools that check for common problems in scientific manuscripts, including information needed to improve transparency and reproducibility. We have combined our tools into a single pipeline, called ScreenIT. We're currently using our tools to screen COVID preprints.
Latest preprint reviews
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Serological Response in Lung Transplant Recipients after Two Doses of SARS-CoV-2 mRNA Vaccines
This article has 11 authors:Reviewed by ScreenIT
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Development of Potent and Effective Synthetic SARS-CoV-2 Neutralizing Nanobodies
This article has 16 authors:Reviewed by ScreenIT
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ROCCA observational study: Early results on safety of Sputnik V vaccine (Gam-COVID-Vac) in the Republic of San Marino using active surveillance
This article has 15 authors:Reviewed by ScreenIT
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Investigating Lipid-Modulating Agents for Prevention or Treatment of COVID-19
This article has 23 authors:Reviewed by ScreenIT
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Highly functional Cellular Immunity in SARS-CoV-2 Non-Seroconvertors is associated with immune protection
This article has 17 authors:Reviewed by ScreenIT
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SARS-CoV-2 ferritin nanoparticle vaccines elicit broad SARS coronavirus immunogenicity
This article has 60 authors:Reviewed by ScreenIT
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Smart Testing with Vaccination: A Bandit Algorithm for Active Sampling for Managing COVID-19
This article has 3 authors:Reviewed by ScreenIT
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American Older Adults in COVID-19 Times: Vulnerability Types, Aging Attitudes, and Emotional Responses
This article has 7 authors:Reviewed by ScreenIT
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Impaired T-cell and antibody immunity after COVID-19 infection in chronically immunosuppressed transplant recipients
This article has 30 authors:Reviewed by ScreenIT
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Evaluation of a multi-species SARS-CoV-2 surrogate virus neutralization test
This article has 15 authors:Reviewed by ScreenIT