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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EVALUATION OF THE PANBIO SARS-COV-2 RAPID ANTIGEN DETECTION TEST IN THE BAHAMAS
This article has 7 authors:Reviewed by ScreenIT
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Transmission of SARS-CoV-2 into and within immigrant households: nationwide registry study from Norway
This article has 6 authors:Reviewed by ScreenIT
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Mode of Presentation and Outcomes of COVID-19 Cases in a Tertiary Hospital in Nigeria
This article has 8 authors:Reviewed by ScreenIT
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Immunogenicity and pre-clinical efficacy of an OMV-based SARS-CoV-2 vaccine
This article has 24 authors:Reviewed by ScreenIT
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Niclosamide reverses SARS-CoV-2 control of lipophagy
This article has 10 authors:Reviewed by ScreenIT
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Drug-free nasal spray as a barrier against SARS-CoV-2 infection: safety and efficacy in human nasal airway epithelia
This article has 8 authors:Reviewed by ScreenIT
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Data-driven analysis of amino acid change dynamics timely reveals SARS-CoV-2 variant emergence
This article has 4 authors:Reviewed by ScreenIT
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COVID-19 vaccine uptake, predictors of vaccination, and self-reported barriers to vaccination among primary school teachers in Poland
This article has 2 authors:Reviewed by ScreenIT
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A Drug Candidate for Treating Adverse Reactions Caused by Pathogenic Antibodies Inducible by SARS-CoV-2 Virus and Vaccines
This article has 7 authors:Reviewed by ScreenIT
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Pathogenic and transcriptomic differences of emerging SARS-CoV-2 variants in the Syrian golden hamster model
This article has 8 authors:Reviewed by ScreenIT