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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Archived dengue serum samples produced false-positive results in SARS-CoV-2 lateral flow-based rapid antibody tests
This article has 7 authors:Reviewed by ScreenIT
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One dose of SARS-CoV-2 vaccine exponentially increases antibodies in individuals who have recovered from symptomatic COVID-19
This article has 7 authors:Reviewed by ScreenIT
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Importance of suppression and mitigation measures in managing COVID-19 outbreaks
This article has 1 author:Reviewed by ScreenIT
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Functional monocytic myeloid-derived suppressor cells increase in blood but not airways and predict COVID-19 severity
This article has 22 authors:Reviewed by ScreenIT
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The impact of the COVID-19 pandemic on mental health and well-being of people living with a long-term physical health condition: a qualitative study
This article has 5 authors:Reviewed by ScreenIT
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The Anxiety and Pain of Fibromyalgia Patients during the COVID-19 Pandemic
This article has 5 authors:Reviewed by ScreenIT
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Heart disease mortality during the early pandemic period in the United States
This article has 6 authors:Reviewed by ScreenIT
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Does sub-Saharan Africa truly defy the forecasts of the COVID-19 pandemic? Response from population data
This article has 6 authors:Reviewed by ScreenIT
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Multiplexed proteomics and imaging of resolving and lethal SARS-CoV-2 infection in the lung
This article has 15 authors:Reviewed by ScreenIT
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Performance of Temporal Artery Temperature Measurement in Ruling Out Fever: Implications for COVID-19 Screening
This article has 4 authors:Reviewed by ScreenIT