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
-
The emergence, spread and vanishing of a French SARS‐CoV‐2 variant exemplifies the fate of RNA virus epidemics and obeys the Mistigri rule
This article has 18 authors:Reviewed by ScreenIT
-
BNT162b2 post-exposure-prophylaxis against COVID-19
This article has 11 authors:Reviewed by ScreenIT
-
Persistence of immunity and impact of third dose of inactivated COVID-19 vaccine against emerging variants
This article has 20 authors:Reviewed by ScreenIT
-
Immune defects associated with lower SARS-CoV-2 BNT162b2 mRNA vaccine response in aged people
This article has 13 authors:Reviewed by ScreenIT
-
A 2-Gene Host Signature for Improved Accuracy of COVID-19 Diagnosis Agnostic to Viral Variants
This article has 15 authors:Reviewed by ScreenIT
-
Modeling the USA Winter 2021 CoVID-19 Resurgence
This article has 1 author:Reviewed by ScreenIT
-
Differential Peripheral Blood Glycoprotein Profiles in Symptomatic and Asymptomatic COVID-19
This article has 16 authors:Reviewed by ScreenIT
-
Persistence of Endogenous SARS-CoV-2 and Pepper Mild Mottle Virus RNA in Wastewater-Settled Solids
This article has 4 authors:Reviewed by ScreenIT
-
Clinical profile and in-hospital outcomes of COVID-19 among adolescents at a tertiary care hospital in India
This article has 8 authors:Reviewed by ScreenIT
-
The impact of demographic factors on numbers of COVID-19 cases and deaths in Europe and the regions of Ukraine
This article has 2 authors:Reviewed by ScreenIT