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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Favipiravir antiviral efficacy against SARS-CoV-2 in a hamster model
This article has 14 authors:Reviewed by ScreenIT
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SARS-CoV-2 Nsp1 binds the ribosomal mRNA channel to inhibit translation
This article has 10 authors:Reviewed by ScreenIT
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Angiotensin-converting enzyme 2 (ACE2) expression increases with age in patients requiring mechanical ventilation
This article has 4 authors:Reviewed by ScreenIT
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The mental health impact of COVID-19 and lockdown-related stressors among adults in the UK
This article has 4 authors:Reviewed by ScreenIT
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Rats and the COVID-19 pandemic: considering the influence of social distancing on a global commensal pest
This article has 10 authors:Reviewed by ScreenIT
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Effect of Systemic Inflammatory Response to SARS-CoV-2 on Lopinavir and Hydroxychloroquine Plasma Concentrations
This article has 18 authors:Reviewed by ScreenIT
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Partial Prediction of the Virus COVID-19 Spread in Russia Based on SIR and SEIR Models
This article has 2 authors:Reviewed by ScreenIT
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Renin–Angiotensin–Aldosterone System Inhibitors and COVID-19 Infection or Hospitalization: A Cohort Study
This article has 10 authors:Reviewed by ScreenIT
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COVID-19 presenting as anosmia and dysgeusia in New York City emergency departments, March - April, 2020
This article has 4 authors:Reviewed by ScreenIT
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Wearable sensor data and self-reported symptoms for COVID-19 detection
This article has 9 authors:Reviewed by ScreenIT