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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COVID-19 Serology at Population Scale: SARS-CoV-2-Specific Antibody Responses in Saliva
This article has 21 authors:Reviewed by ScreenIT
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Prevalence and risk factors for mortality related to COVID-19 in a severely affected area of Madrid, Spain
This article has 15 authors:Reviewed by ScreenIT
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Spurious Correlation? A review of the relationship between Vitamin D and Covid-19 infection and mortality
This article has 2 authors:Reviewed by ScreenIT
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Serum Responses of Children With Kawasaki Disease Against Severe Acute Respiratory Syndrome Coronavirus 2 Proteins
This article has 5 authors:Reviewed by ScreenIT
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Seroprevalence of antibodies against SARS-CoV-2 among public community and health-care workers in Alzintan City of Libya
This article has 5 authors:Reviewed by ScreenIT
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Effect of Socioeconomic and Ethnic Characteristics on COVID-19 Infection: the Case of the Ultra-Orthodox and the Arab Communities in Israel
This article has 5 authors:Reviewed by ScreenIT
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Age, gender and COVID-19 infections
This article has 5 authors:Reviewed by ScreenIT
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Investigational Treatments for COVID‐19 may Increase Ventricular Arrhythmia Risk Through Drug Interactions
This article has 7 authors:Reviewed by ScreenIT
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COVID-19 impact on consecutive neurological patients admitted to the emergency department
This article has 45 authors:Reviewed by ScreenIT
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What Can We Learn from the Time Evolution of COVID‐19 Epidemic in Slovenia?
This article has 1 author:Reviewed by ScreenIT