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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Projection of COVID-19 Cases and Deaths in the US as Individual States Re-open May 4, 2020
This article has 4 authors:Reviewed by ScreenIT
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Cooperative virus propagation in COVID-19 transmission
This article has 2 authors:Reviewed by ScreenIT
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The SARS-CoV-2-like virus found in captive pangolins from Guangdong should be better sequenced
This article has 1 author:Reviewed by ScreenIT
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A mouse-adapted model of SARS-CoV-2 to test COVID-19 countermeasures
This article has 19 authors:Reviewed by ScreenIT
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The landscape of host genetic factors involved in immune response to common viral infections
This article has 9 authors:Reviewed by ScreenIT
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Urban Air Pollution May Enhance COVID-19 Case-Fatality and Mortality Rates in the United States
This article has 11 authors:Reviewed by ScreenIT
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Development of a clinical decision support system for severity risk prediction and triage of COVID-19 patients at hospital admission: an international multicentre study
This article has 29 authors:Reviewed by ScreenIT
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Immune Alterations in a Patient with SARS-CoV-2-Related Acute Respiratory Distress Syndrome
This article has 14 authors:Reviewed by ScreenIT
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The disproportionate rise in COVID-19 cases among Hispanic/Latinx in disadvantaged communities of Orange County, California: A socioeconomic case-series
This article has 15 authors:Reviewed by ScreenIT
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A noncompeting pair of human neutralizing antibodies block COVID-19 virus binding to its receptor ACE2
This article has 25 authors:Reviewed by ScreenIT