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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365 days with COVID-19 in Iran: data analysis and epidemic curves
This article has 2 authors:Reviewed by ScreenIT
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COVID-19 IN IRAQ, THE RURAL INITIATION (AL-MUTHANNA PROVINCE AS AN EXAMPLE)
This article has 8 authors:Reviewed by ScreenIT
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Seroprevalence of SARS-CoV-2 infection in Cincinnati Ohio USA from August to December 2020
This article has 24 authors:Reviewed by ScreenIT
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Modeling COVID-19 in Iran using Particle Swarm Optimization algorithm
This article has 2 authors:Reviewed by ScreenIT
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ReCOVer study: A Cross-sectional Observational Study to Identify the Re habilitation Need in Post-discharge COV ID-19 Survivors
This article has 6 authors:Reviewed by ScreenIT
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Role of combining anticoagulant and antiplatelet agents in COVID-19 treatment: a rapid review
This article has 6 authors:Reviewed by ScreenIT
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The nonstructural protein 5 of coronaviruses antagonizes GSDMD-mediated pyroptosis by cleaving and inactivating its pore-forming p30 fragment
This article has 13 authors:Reviewed by ScreenIT
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Higher COVID-19 vaccination rates are linked to decreased county-level COVID-19 incidence across USA
This article has 10 authors:Reviewed by ScreenIT
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Multi-clonal SARS-CoV-2 neutralization by antibodies isolated from severe COVID-19 convalescent donors
This article has 28 authors:Reviewed by ScreenIT
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mRNA-1273 vaccine induces neutralizing antibodies against spike mutants from global SARS-CoV-2 variants
This article has 14 authors:Reviewed by ScreenIT