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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Effects of SARS‑CoV‑2 mRNA vaccines on platelet polyphosphate levels and inflammation: A pilot study
This article has 10 authors:Reviewed by ScreenIT
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Persistent Oxidative Stress and Inflammasome Activation in CD14highCD16− Monocytes From COVID-19 Patients
This article has 18 authors:Reviewed by ScreenIT
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Molecular architecture and dynamics of SARS-CoV-2 envelope by integrative modeling
This article has 9 authors:Reviewed by ScreenIT
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Spread of SARS-CoV-2 Delta variant infections bearing the S:E484Q and S:T95I mutations in July and August 2021 in France
This article has 11 authors:Reviewed by ScreenIT
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Social capital dimensions are differentially associated with COVID-19 vaccinations, masks, and physical distancing
This article has 2 authors:Reviewed by ScreenIT
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Severe Acute Respiratory Syndrome Coronavirus-2 seroprevalence in South-Central Uganda, during 2019–2021
This article has 26 authors:Reviewed by ScreenIT
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High seroconversion rates amongst black and Hispanics with hematologic malignancies after SARS-CoV-2 vaccination
This article has 20 authors:Reviewed by ScreenIT
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mRNA COVID-19 Vaccination and Development of CMR-confirmed Myopericarditis
This article has 12 authors:Reviewed by ScreenIT
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Intronization enhances expression of S-protein and other transgenes challenged by cryptic splicing
This article has 7 authors:Reviewed by ScreenIT
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Buildout and integration of an automated high-throughput CLIA laboratory for SARS-CoV-2 testing on a large urban campus
This article has 37 authors:Reviewed by ScreenIT