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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Mask mandates can limit COVID spread: Quantitative assessment of month-over-month effectiveness of governmental policies in reducing the number of new COVID-19 cases in 37 US States and the District of Columbia
This article has 3 authors:Reviewed by ScreenIT
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Fluorescence-detection size-exclusion chromatography utilizing nanobody technology for expression screening of membrane proteins
This article has 6 authors:Reviewed by ScreenIT
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Modelling the effect of lockdown
This article has 2 authors:Reviewed by ScreenIT
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SARS-CoV-2 structural coverage map reveals state changes that disrupt host immunity
This article has 12 authors:Reviewed by ScreenIT
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Development and validation of a knowledge-driven risk calculator for critical illness in COVID-19 patients
This article has 10 authors:Reviewed by ScreenIT
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Molecular detection of SARS-CoV-2 using a reagent-free approach
This article has 5 authors:Reviewed by ScreenIT
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Modeling the effect of contaminated objects for the transmission dynamics of COVID-19 pandemic with self protection behavior changes
This article has 3 authors:Reviewed by ScreenIT
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Horizontal gene transfer and recombination analysis of SARS-CoV-2 genes helps discover its close relatives and shed light on its origin
This article has 4 authors:Reviewed by ScreenIT
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Ongoing Positive Selection Drives the Evolution of SARS-CoV-2 Genomes
This article has 10 authors:Reviewed by ScreenIT
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Lockdown measures and relative changes in the age-specific incidence of SARS-CoV-2 in Spain
This article has 10 authors:Reviewed by ScreenIT