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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Ultrapotent miniproteins targeting the SARS-CoV-2 receptor-binding domain protect against infection and disease
This article has 18 authors:Reviewed by ScreenIT
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Resilience of countries to COVID-19 correlated with trust
This article has 3 authors:Reviewed by ScreenIT
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Unique mutational changes in SARS-CoV-2 genome: A case study for the largest state of India
This article has 14 authors:Reviewed by ScreenIT
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Evidence for antibody as a protective correlate for COVID-19 vaccines
This article has 8 authors:Reviewed by ScreenIT
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Will the large‐scale vaccination succeed in containing the COVID‐19 pandemic and how soon?
This article has 5 authors:Reviewed by ScreenIT
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Differential effect of corticosteroid treatment on Influenza, SARS, MERS, and SARS-CoV-2 patients: A meta-analysis and systematic review
This article has 11 authors:Reviewed by ScreenIT
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A generalizable data assembly algorithm for infectious disease outbreaks
This article has 2 authors:Reviewed by ScreenIT
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Thromboembolism risk among patients with diabetes/stress hyperglycemia and COVID-19
This article has 19 authors:Reviewed by ScreenIT
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Forecasting the Epidemiological Impact of Coronavirus Disease (COVID-19): Pre-vaccination Era
This article has 1 author:Reviewed by ScreenIT
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Surveillance of SARS-CoV-2 lineage B.1.1.7 in Slovakia using a novel, multiplexed RT-qPCR assay
This article has 26 authors:Reviewed by ScreenIT