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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Divide in Vaccine Belief in COVID-19 Conversations: Implications for Immunization Plans
This article has 2 authors:Reviewed by ScreenIT
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Epidemiological and cohort study finds no association between COVID-19 and Guillain-Barré syndrome
This article has 42 authors:Reviewed by ScreenIT
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Retrospective study of the first wave of COVID-19 in Spain: analysis of counterfactual scenarios
This article has 8 authors:Reviewed by ScreenIT
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Application of a Semi-Empirical Dynamic Model to Forecast the Propagation of the COVID-19 Epidemics in Spain
This article has 3 authors:Reviewed by ScreenIT
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SARS-CoV-2 Cell Entry Depends on ACE2 and TMPRSS2 and Is Blocked by a Clinically Proven Protease Inhibitor
This article has 13 authors:Reviewed by ScreenIT
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Presenting features of COVID-19 in older people: relationships with frailty, inflammation and mortality
This article has 8 authors:Reviewed by ScreenIT
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Effect of β-chitosan on the binding interaction between SARS-CoV-2 S-RBD and ACE2
This article has 15 authors:Reviewed by ScreenIT
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The Role of Nutrition in COVID-19 Susceptibility and Severity of Disease: A Systematic Review
This article has 18 authors:Reviewed by ScreenIT
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COVID-19 Pandemic in University Hospital: Is There an Effect on The Medical Interns?
This article has 4 authors:Reviewed by ScreenIT
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Transmission dynamics of SARS-CoV-2 within-host diversity in two major hospital outbreaks in South Africa
This article has 19 authors:Reviewed by ScreenIT