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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SARS-CoV-2 spike protein induces brain pericyte immunoreactivity in absence of productive viral infection
This article has 8 authors:Reviewed by ScreenIT
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The K18-Human ACE2 Transgenic Mouse Model Recapitulates Non-severe and Severe COVID-19 in Response to an Infectious Dose of the SARS-CoV-2 Virus
This article has 21 authors:Reviewed by ScreenIT
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Prevalence of anxiety, depression, and stress among teachers during the COVID-19 pandemic
This article has 4 authors:Reviewed by ScreenIT
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Infection, recovery and re-infection of farmed mink with SARS-CoV-2
This article has 15 authors:Reviewed by ScreenIT
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Binding of SARS-CoV-2 fusion peptide to host membranes
This article has 3 authors:Reviewed by ScreenIT
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Metagenomic Sequencing To Detect Respiratory Viruses in Persons under Investigation for COVID-19
This article has 8 authors:Reviewed by ScreenIT
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Coronavirus GenBrowser for monitoring the transmission and evolution of SARS-CoV-2
This article has 21 authors:Reviewed by ScreenIT
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High-altitude is associated with better short-term survival in critically ill COVID-19 patients admitted to the ICU
This article has 13 authors:Reviewed by ScreenIT
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COVID-19 FATALITY RISK: WHY IS AUSTRALIA’S LOWER THAN SOUTH KOREA?
This article has 2 authors:Reviewed by ScreenIT
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COVIDHunter: COVID-19 Pandemic Wave Prediction and Mitigation via Seasonality Aware Modeling
This article has 5 authors:Reviewed by ScreenIT