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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Fraction of COVID-19 hospitalizations and deaths attributable to chronic diseases
This article has 10 authors:Reviewed by ScreenIT
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Acceptability of COVID-19 Vaccination among Health Care Workers in Ghana
This article has 4 authors:Reviewed by ScreenIT
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Point‐of‐Care Ultrasound Predicts Clinical Outcomes in Patients With COVID ‐19
This article has 15 authors:Reviewed by ScreenIT
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Evaluation of SARS-CoV-2 entry, inflammation and new therapeutics in human lung tissue cells
This article has 15 authors:Reviewed by ScreenIT
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Genome-Scale Identification of SARS-CoV-2 and Pan-coronavirus Host Factor Networks
This article has 15 authors:Reviewed by ScreenIT
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Inflammatory profiles across the spectrum of disease reveal a distinct role for GM-CSF in severe COVID-19
This article has 379 authors:Reviewed by ScreenIT
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Performance Decay of Molecular Assays Near the Limit of Detection: Probabilistic Modeling using Real-World COVID-19 Data
This article has 4 authors:Reviewed by ScreenIT
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Risk quantification for SARS-CoV-2 infection through airborne transmission in university settings
This article has 11 authors:Reviewed by ScreenIT
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Verification of the Abbott Alinity m Resp-4-Plex assay for detection of SARS-CoV-2, influenza A/B, and respiratory syncytial virus
This article has 4 authors:Reviewed by ScreenIT
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Categorizing the Status of COVID-19 Outbreaks Around the World
This article has 4 authors:Reviewed by ScreenIT