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 Epidemics Monitored Through the Logarithmic Growth Rate and SIR Model
This article has 1 author:Reviewed by ScreenIT
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Association of Initial Clinical Characteristics with the Need for the Intensive Care Unit and Hospitalization in Patients Presenting to the Emergency Department with Acute Symptomatic COVID-19
This article has 7 authors:Reviewed by ScreenIT
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Genomic Surveillance in Japan of AY.29—A New Sub-lineage of SARS-CoV-2 Delta Variant with C5239T and T5514C Mutations
This article has 2 authors:Reviewed by ScreenIT
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Estimates of Presumed Population Immunity to SARS-CoV-2 by State in the United States, August 2021
This article has 9 authors:Reviewed by ScreenIT
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Asthma as a risk factor for hospitalization in children with COVID‐19: A nested case‐control study
This article has 11 authors:Reviewed by ScreenIT
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Impact of Vaccination and Testing Levels on the Dynamics of the COVID-19 Pandemic and its Cessation
This article has 2 authors:Reviewed by ScreenIT
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Deleterious drugs in COVID-19: a rapid systematic review and meta-analysis
This article has 5 authors:Reviewed by ScreenIT
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The Delta Variant Had Negligible Impact on COVID-19 Vaccine Effectiveness in the USA
This article has 4 authors:Reviewed by ScreenIT
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Comparative analysis of human immune responses following SARS-CoV-2 vaccination with BNT162b2, mRNA-1273, or Ad26.COV2.S
This article has 12 authors:Reviewed by ScreenIT
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Consequences of COVID-19 vaccine allocation inequity in Chicago
This article has 5 authors:Reviewed by ScreenIT