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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Epidemiological, Clinical, Radiological Characteristics and Outcomes of Medical Staff with COVID-19 in Wuhan, China: Analysis of 101 Cases
This article has 10 authors:Reviewed by ScreenIT
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Rigidity, normal modes and flexible motion of a SARS-CoV-2 (COVID-19) protease structure
This article has 1 author:Reviewed by ScreenIT
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Novel and potent inhibitors targeting DHODH are broad-spectrum antivirals against RNA viruses including newly-emerged coronavirus SARS-CoV-2
This article has 25 authors:Reviewed by ScreenIT
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Early, low-dose and short-term application of corticosteroid treatment in patients with severe COVID-19 pneumonia: single-center experience from Wuhan, China
This article has 8 authors:Reviewed by ScreenIT
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The inhaled corticosteroid ciclesonide blocks coronavirus RNA replication by targeting viral NSP15
This article has 8 authors:Reviewed by ScreenIT
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A human monoclonal antibody blocking SARS-CoV-2 infection
This article has 10 authors:Reviewed by ScreenIT
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Development of Reverse Transcription Loop-Mediated Isothermal Amplification Assays Targeting Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)
This article has 7 authors:Reviewed by ScreenIT
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The SARS-CoV-2 Exerts a Distinctive Strategy for Interacting with the ACE2 Human Receptor
This article has 3 authors:Reviewed by ScreenIT
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Quantifying SARS-CoV-2 transmission suggests epidemic control with digital contact tracing
This article has 9 authors:Reviewed by ScreenIT
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Retrospective Analysis of Clinical Features in 101 Death Cases with COVID-19
This article has 11 authors:Reviewed by ScreenIT