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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SARS-CoV-2 Seroprevalence in Relation to Timing of Symptoms
This article has 38 authors:Reviewed by ScreenIT
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Pooling RT-qPCR testing for SARS-CoV-2 in 1000 individuals of healthy and infection-suspected patients
This article has 13 authors:Reviewed by ScreenIT
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Oncologic immunomodulatory agents in patients with cancer and COVID-19
This article has 15 authors:Reviewed by ScreenIT
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SalivaDirect: A simplified and flexible platform to enhance SARS-CoV-2 testing capacity
This article has 86 authors:Reviewed by ScreenIT
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BCG Vaccine Protection from Severe Coronavirus Disease 2019 (COVID19)
This article has 3 authors:Reviewed by ScreenIT
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Time courses of COVID-19 infection and local variation in socioeconomic and health disparities in England
This article has 4 authors:Reviewed by ScreenIT
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Evaluating COVID-19 reporting data in the context of testing strategies across 31 low- and middle-income countries
This article has 4 authors:Reviewed by ScreenIT
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Field evaluation of a rapid antigen test (Panbio™ COVID-19 Ag Rapid Test Device) for COVID-19 diagnosis in primary healthcare centres
This article has 14 authors:Reviewed by ScreenIT
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A Comparative Study of Real-Time RT-PCR–Based SARS-CoV-2 Detection Methods and Its Application to Human-Derived and Surface Swabbed Material
This article has 11 authors:Reviewed by ScreenIT
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In Silico Modeling of Coronavirus Disease 2019 Acute Respiratory Distress Syndrome: Pathophysiologic Insights and Potential Management Implications
This article has 9 authors:Reviewed by ScreenIT