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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Sex and Gender Differences in Testing, Hospital Admission, Clinical Presentation, and Drivers of Severe Outcomes From COVID-19
This article has 14 authors:Reviewed by ScreenIT
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Leveraging Genetic Data to Elucidate the Relationship Between COVID‐19 and Ischemic Stroke
This article has 9 authors:Reviewed by ScreenIT
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COVID-19 Vaccine’s Gender Paradox
This article has 4 authors:Reviewed by ScreenIT
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An Antioxidant Enzyme Therapeutic for COVID‐19
This article has 29 authors:Reviewed by ScreenIT
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Nonpharmaceutical Interventions Remain Essential to Reducing Coronavirus Disease 2019 Burden Even in a Well-Vaccinated Society: A Modeling Study
This article has 5 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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Single-Cell RNA Expression Profiling of ACE2, the Receptor of SARS-CoV-2
This article has 6 authors:Reviewed by ScreenIT
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Contrasting Epidemiology and Population Genetics of COVID-19 Infections Defined by Multilocus Genotypes in SARS-CoV-2 Genomes Sampled Globally
This article has 4 authors:Reviewed by ScreenIT
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Modelling the impact of extending dose intervals for COVID-19 vaccines in Canada
This article has 7 authors:Reviewed by ScreenIT
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From first to second wave: follow-up of the prospective COVID-19 cohort (KoCo19) in Munich (Germany)
This article has 125 authors:Reviewed by ScreenIT
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Bromhexine Hydrochloride Prophylaxis of COVID-19 for Medical Personnel: A Randomized Open-Label Study
This article has 8 authors:Reviewed by ScreenIT