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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Structural basis for the inhibition of the SARS-CoV-2 RNA-dependent RNA polymerase by favipiravir-RTP
This article has 15 authors:Reviewed by ScreenIT
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Clinical prediction rule for SARS-CoV-2 infection from 116 U.S. emergency departments 2-22-2021
This article has 34 authors:Reviewed by ScreenIT
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When will the Covid-19 epidemic fade out?
This article has 1 author:Reviewed by ScreenIT
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Detection of SARS-Cov-2 RNA in serum is associated with increased mortality risk in hospitalized COVID-19 patients
This article has 30 authors:Reviewed by ScreenIT
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RT qLAMP—Direct Detection of SARS-CoV-2 in Raw Sewage
This article has 2 authors:Reviewed by ScreenIT
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Single-nucleotide conservation state annotation of the SARS-CoV-2 genome
This article has 2 authors:Reviewed by ScreenIT
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Neutralising SARS-CoV-2 RBD-specific antibodies persist for at least six months independently of symptoms in adults
This article has 12 authors:Reviewed by ScreenIT
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Routine SARS-CoV-2 wastewater surveillance results in Turkey to follow Covid-19 outbreak
This article has 8 authors:Reviewed by ScreenIT
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Temporal Kinetics of RNAemia and Associated Systemic Cytokines in Hospitalized COVID-19 Patients
This article has 13 authors:Reviewed by ScreenIT
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Single‐cell analyses reveal SARS‐CoV‐2 interference with intrinsic immune response in the human gut
This article has 14 authors:Reviewed by ScreenIT