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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Acid pH Increases SARS-CoV-2 Infection and the Risk of Death by COVID-19
This article has 21 authors:Reviewed by ScreenIT
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Transcriptional and epi-transcriptional dynamics of SARS-CoV-2 during cellular infection
This article has 16 authors:Reviewed by ScreenIT
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Real-time analysis of a mass vaccination effort confirms the safety of FDA-authorized mRNA COVID-19 vaccines
This article has 26 authors:Reviewed by ScreenIT
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App-based symptom tracking to optimize SARS-CoV-2 testing strategy using machine learning
This article has 10 authors:Reviewed by ScreenIT
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The spatio-temporal landscape of lung pathology in SARS-CoV-2 infection
This article has 7 authors:Reviewed by ScreenIT
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The impact of the COVID-19 pandemic on families in Germany
This article has 11 authors:Reviewed by ScreenIT
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Evaluation of a novel multiplexed assay for determining IgG levels and functional activity to SARS-CoV-2
This article has 10 authors:Reviewed by ScreenIT
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The Impact of Covid-19 Pandemic on the Preventive Services in Qatar
This article has 8 authors:Reviewed by ScreenIT
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Human Safety, Tolerability, and Pharmacokinetics of Molnupiravir, a Novel Broad-Spectrum Oral Antiviral Agent with Activity against SARS-CoV-2
This article has 9 authors:Reviewed by ScreenIT
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Comparing Public Perceptions and Preventive Behaviors During the Early Phase of the COVID-19 Pandemic in Hong Kong and the United Kingdom: Cross-sectional Survey Study
This article has 8 authors:Reviewed by ScreenIT