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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Antibodies to the SARS-CoV-2 receptor-binding domain that maximize breadth and resistance to viral escape
This article has 46 authors:Reviewed by ScreenIT
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Agreement between commercially available ELISA and in-house Luminex SARS-CoV-2 antibody immunoassays
This article has 10 authors:Reviewed by ScreenIT
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Monitoring carbon dioxide to quantify the risk of indoor airborne transmission of COVID-19
This article has 6 authors:Reviewed by ScreenIT
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Seroepidemiology of SARS-CoV-2 infections in an urban Nicaraguan population
This article has 13 authors:Reviewed by ScreenIT
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The within-host viral kinetics of SARS-CoV-2
This article has 4 authors:Reviewed by ScreenIT
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Extracorporeal Blood Purification in Moderate and Severe COVID-19 Patients: A Prospective Cohort Study
This article has 11 authors:Reviewed by ScreenIT
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SARS-CoV-2-specific circulating T follicular helper cells correlate with neutralizing antibodies and increase during early convalescence
This article has 10 authors:Reviewed by ScreenIT
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No Evidence of Coronaviruses or Other Potentially Zoonotic Viruses in Sunda pangolins (Manis javanica) Entering the Wildlife Trade via Malaysia
This article has 13 authors: -
Screening of candidate host cell membrane proteins involved in SARS-CoV-2 entry
This article has 3 authors:Reviewed by ScreenIT
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Modeling of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Proteins by Machine Learning and Physics-Based Refinement
This article has 2 authors:Reviewed by ScreenIT