ScreenIT
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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Metformin Use Is Associated With Reduced Mortality in a Diverse Population With COVID-19 and Diabetes
This article has 6 authors:Reviewed by ScreenIT
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Prolonged presence of replication‐competent SARS‐CoV‐2 in mildly symptomatic individuals: A report of two cases
This article has 21 authors:Reviewed by ScreenIT
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Exit strategies: optimising feasible surveillance for detection, elimination, and ongoing prevention of COVID-19 community transmission
This article has 8 authors:Reviewed by ScreenIT
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Emergence and expansion of highly infectious spike:D614G mutant SARS-CoV-2 in central India
This article has 19 authors:Reviewed by ScreenIT
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Do not neglect SARS-CoV-2 hospitalization and fatality risks in the middle-aged adult population
This article has 9 authors:Reviewed by ScreenIT
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Assessment of effective mitigation and prediction of the spread of SARS-CoV-2 in Germany using demographic information and spatial resolution
This article has 20 authors:Reviewed by ScreenIT
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Growth of respiratory droplets in cold and humid air
This article has 6 authors:Reviewed by ScreenIT
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Pulmonary stromal expansion and intra-alveolar coagulation are primary causes of Covid-19 death
This article has 14 authors:Reviewed by ScreenIT
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Sustained cellular immune dysregulation in individuals recovering from SARS-CoV-2 infection
This article has 15 authors:Reviewed by ScreenIT
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Rapid development of SARS-CoV-2 receptor binding domain-conjugated nanoparticle vaccine candidate
This article has 19 authors:Reviewed by ScreenIT