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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Human neutralizing antibodies elicited by SARS-CoV-2 infection
This article has 24 authors:Reviewed by ScreenIT
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Analysis of Serologic Cross-Reactivity Between Common Human Coronaviruses and SARS-CoV-2 Using Coronavirus Antigen Microarray
This article has 13 authors:Reviewed by ScreenIT
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Single-Cell RNA-seq Reveals Angiotensin-Converting Enzyme 2 and Transmembrane Serine Protease 2 Expression in TROP2+ Liver Progenitor Cells: Implications in Coronavirus Disease 2019-Associated Liver Dysfunction
This article has 11 authors:Reviewed by ScreenIT
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Imbalanced Host Response to SARS-CoV-2 Drives Development of COVID-19
This article has 15 authors:Reviewed by ScreenIT
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Nonrelocatable Occupations at Increased Risk During Pandemics: United States, 2018
This article has 1 author:Reviewed by ScreenIT
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High risk of infection caused Posttraumatic Stress symptoms in individuals with poor sleep quality: A study on influence of Coronavirus disease (COVID-19) in China
This article has 12 authors:Reviewed by ScreenIT
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Infection Control of 2019 Novel Corona Virus Disease (COVID-19) in Cancer Patients undergoing Radiotherapy in Wuhan
This article has 7 authors:Reviewed by ScreenIT
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First clinical study using HCV protease inhibitor danoprevir to treat COVID-19 patients
This article has 8 authors:Reviewed by ScreenIT
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Characterisation of the transcriptome and proteome of SARS-CoV-2 reveals a cell passage induced in-frame deletion of the furin-like cleavage site from the spike glycoprotein
This article has 11 authors:Reviewed by ScreenIT