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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Effect on the conformations of the spike protein of SARS‐CoV‐2 due to mutation
This article has 2 authors:Reviewed by ScreenIT
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Detection Of SARS-COV-2 Variants Of Concern In Wastewater Of Leuven, Belgium
This article has 12 authors:Reviewed by ScreenIT
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Factors Related to Stress in Children with Online Media Learning Methods during a Pandemic at Jaya Mulya 1 Elementary School, Karawang-Indonesia
This article has 2 authors:Reviewed by ScreenIT
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Biosynthetic proteins targeting the SARS-CoV-2 spike as anti-virals
This article has 22 authors:Reviewed by ScreenIT
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Investigating the evolutionary origins of the first three SARS-CoV-2 variants of concern
This article has 5 authors:Reviewed by ScreenIT
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Early detection of fraudulent COVID-19 products from Twitter chatter
This article has 6 authors:Reviewed by ScreenIT
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COVID-19 Vaccine effectiveness against symptomatic infection and hospitalization in Belgium, July 2021-APRIL 2022
This article has 11 authors:Reviewed by ScreenIT
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Three-dose vaccination-induced immune responses protect against SARS-CoV-2 Omicron BA.2
This article has 16 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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Inhaled CO 2 concentration while wearing face masks: a pilot study using capnography
This article has 5 authors:Reviewed by ScreenIT
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Comparative Study Between the First and Second Wave of COVID-19 Deaths in India: A Single Center Study
This article has 7 authors:Reviewed by ScreenIT