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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County-level exposures to greenness and associations with COVID-19 incidence and mortality in the United States
This article has 8 authors:Reviewed by ScreenIT
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Amplicon contamination in labs masquerades as COVID19 in surveillance tests
This article has 13 authors:Reviewed by ScreenIT
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A Whole Virion Vaccine for COVID-19 Produced via a Novel Inactivation Method and Preliminary Demonstration of Efficacy in an Animal Challenge Model
This article has 16 authors:Reviewed by ScreenIT
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Association between self-reported signs and symptoms and SARS-CoV-2 antibody detection in UK key workers
This article has 19 authors:Reviewed by ScreenIT
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The Impact of Vaccination on Coronavirus Disease 2019 (COVID-19) Outbreaks in the United States
This article has 11 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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Clarifying predictions for COVID-19 from testing data: The example of New York State
This article has 2 authors:Reviewed by ScreenIT
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Changes in the rate of cardiometabolic and pulmonary events during the COVID-19 pandemic
This article has 34 authors:Reviewed by ScreenIT
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Increasing SARS-CoV-2 RT-qPCR testing capacity by sample pooling
This article has 8 authors:Reviewed by ScreenIT
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How Many Lives Has Lockdown Saved in the UK?
This article has 2 authors:Reviewed by ScreenIT
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Lack of Trust, Conspiracy Beliefs, and Social Media Use Predict COVID-19 Vaccine Hesitancy
This article has 8 authors:Reviewed by ScreenIT