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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GP73 is a glucogenic hormone contributing to SARS-CoV-2-induced hyperglycemia
This article has 43 authors:Reviewed by ScreenIT
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COVID-19 and acute kidney injury in German hospitals 2020
This article has 3 authors:Reviewed by ScreenIT
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Identification of DAXX as a restriction factor of SARS-CoV-2 through a CRISPR/Cas9 screen
This article has 25 authors:Reviewed by ScreenIT
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Outbreaks of COVID-19 variants in US prisons: a mathematical modelling analysis of vaccination and reopening policies
This article has 10 authors:Reviewed by ScreenIT
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Prolonged SARS-CoV-2 RNA virus shedding and lymphopenia are hallmarks of COVID-19 in cancer patients with poor prognosis
This article has 69 authors:Reviewed by ScreenIT
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Transmission of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) from pre and asymptomatic infected individuals: a systematic review
This article has 9 authors:Reviewed by ScreenIT
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Longitudinal SARS-CoV-2 infection study in a German medical school
This article has 24 authors:Reviewed by ScreenIT
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SARS-CoV-2 genomes from Saudi Arabia implicate nucleocapsid mutations in host response and increased viral load
This article has 36 authors:Reviewed by ScreenIT
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COVID-19 wastewater surveillance in rural communities: Comparison of lagoon and pumping station samples
This article has 11 authors:Reviewed by ScreenIT
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Risk assessment for long- and short-range airborne transmission of SARS-CoV-2, indoors and outdoors
This article has 10 authors:Reviewed by ScreenIT