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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Tracing the trajectories of SARS-CoV-2 variants of concern between December 2020 and September 2021 in the Canary Islands (Spain)
This article has 13 authors:Reviewed by ScreenIT
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Real-world Effectiveness of Casirivimab and Imdevimab in Patients With COVID-19 in the Ambulatory Setting: An Analysis of Two Large US National Claims Databases
This article has 8 authors:Reviewed by ScreenIT
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Study on the usefulness of Direct Saliva sample Collection (DiSC) by polyester swab
This article has 7 authors:Reviewed by ScreenIT
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Olfactory Training in Post-COVID-19 Persistent Olfactory Disorders: Value Normalization for Threshold but Not Identification
This article has 16 authors:Reviewed by ScreenIT
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Different efficacies of neutralizing antibodies and antiviral drugs on SARS-CoV-2 Omicron subvariants, BA.1 and BA.2
This article has 23 authors:Reviewed by ScreenIT
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Presence of Symptoms 6 Weeks After COVID-19 Among Vaccinated and Unvaccinated U.S. Healthcare Personnel
This article has 14 authors:Reviewed by ScreenIT
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Psychosocial factors associated with mental health and quality of life during the COVID-19 pandemic among low-income urban dwellers in Peninsular Malaysia
This article has 6 authors:Reviewed by ScreenIT
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Mitoquinone mesylate targets SARS-CoV-2 infection in preclinical models
This article has 18 authors:Reviewed by ScreenIT
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CoviVac vaccination induces production of neutralizing antibodies against Delta and Omicron variants of SARS-CoV-2
This article has 15 authors:Reviewed by ScreenIT
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Effectiveness of the third dose of BNT162b2 vaccine on neutralizing Omicron variant in the Japanese population
This article has 14 authors:Reviewed by ScreenIT