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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A Multi-hospital Study in Wuhan, China: Protective Effects of Non-menopause and Female Hormones on SARS-CoV-2 infection
This article has 17 authors:Reviewed by ScreenIT
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A considerable proportion of individuals with asymptomatic SARS-CoV-2 infection in Tibetan population
This article has 7 authors:Reviewed by ScreenIT
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COVID-19 Patients: A Systematic Review and Meta-Analysis of Laboratory Findings, Comorbidities, and Clinical Outcomes Comparing Medical Staff versus the General Population
This article has 3 authors:Reviewed by ScreenIT
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Advice from a systems-biology model of the corona epidemics
This article has 2 authors:Reviewed by ScreenIT
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Mitigation and herd immunity strategy for COVID-19 is likely to fail
This article has 17 authors:Reviewed by ScreenIT
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Effects of temperature on COVID-19 transmission
This article has 4 authors:Reviewed by ScreenIT
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Spread of SARS-CoV-2 in the Icelandic Population
This article has 40 authors:Reviewed by ScreenIT
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First month of the epidemic caused by COVID-19 in Italy: current status and real-time outbreak development forecast
This article has 1 author:Reviewed by ScreenIT
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Risks of ACE Inhibitor and ARB Usage in COVID‐19: Evaluating the Evidence
This article has 2 authors:Reviewed by ScreenIT
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The early scientific literature response to the novel Coronavirus outbreak: who published what?
This article has 3 authors:Reviewed by ScreenIT