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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Simulating Retarded SEIRS model for COVID-19: will the second epidemic happen?
This article has 1 author:Reviewed by ScreenIT
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Prevalence and Factors Associated with Mental Health Impact of COVID-19 Pandemic in Bangladesh: A Survey-Based Cross- Sectional Study
This article has 13 authors:Reviewed by ScreenIT
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Covid-19 Pandemic- Pits and falls of major states of India
This article has 2 authors:Reviewed by ScreenIT
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Seroprevalence of anti–SARS-CoV-2 IgG antibodies in Kenyan blood donors
This article has 39 authors:Reviewed by ScreenIT
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Analysis and Prediction of the COVID-19 outbreak in Pakistan
This article has 3 authors:Reviewed by ScreenIT
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Characteristics Associated With Household Transmission of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in Ontario, Canada: A Cohort Study
This article has 8 authors: -
A Two-Phase Stochastic Dynamic Model for COVID-19 Mid-Term Policy Recommendations in Greece: A Pathway towards Mass Vaccination
This article has 4 authors:Reviewed by ScreenIT
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Association of COVID-19 spread with on-demand testing
This article has 1 author:Reviewed by ScreenIT
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Managing the COVID-19 health crisis: a survey of Swiss hospital pharmacies
This article has 4 authors:Reviewed by ScreenIT
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Antibody-induced procoagulant platelets in severe COVID-19 infection
This article has 17 authors:Reviewed by ScreenIT