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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SARS-CoV-2 Seroconversion in Response to Infection and Vaccination: a Time Series Local Study in Brazil
This article has 17 authors:Reviewed by ScreenIT
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Current epidemiological situation of COVID-19 in the Republic of Belarus: characteristics of the epidemic process, sanitary and anti-epidemic measures
This article has 8 authors:Reviewed by ScreenIT
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Cellular and Humoral Immune Response to a Third Dose of BNT162b2 COVID-19 Vaccine – A Prospective Observational Study
This article has 8 authors:Reviewed by ScreenIT
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Possible Role of P-selectin Adhesion in Long-COVID: A Comparative Analysis of a Long-COVID Case Versus an Asymptomatic Post-COVID Case
This article has 7 authors:Reviewed by ScreenIT
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Prevalence and Predictors of Depression, Anxiety and Stress among Elderly in the aftermath of COVID-19: A Quantitative Study from Central India
This article has 9 authors:Reviewed by ScreenIT
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Spatial patterns of excess mortality in the first year of the COVID-19 pandemic in Germany
This article has 2 authors:Reviewed by ScreenIT
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Emergency Medical Services Prehospital Response to the COVID-19 Pandemic in the US: A Brief Literature Review
This article has 8 authors:Reviewed by ScreenIT
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Pharmacokinetics of favipiravir in adults with mild COVID-19 in Thailand
This article has 9 authors:Reviewed by ScreenIT
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Cross-sector decision landscape in response to COVID-19: A qualitative network mapping analysis of North Carolina decision-makers
This article has 8 authors:Reviewed by ScreenIT
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Time-Varying Risk of Death After SARS-CoV-2-Infection in Long-Term Care Facility Residents: A Matched Cohort Study
This article has 6 authors:Reviewed by ScreenIT