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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Patterns of the COVID-19 pandemic spread around the world: exponential versus power laws
This article has 3 authors:Reviewed by ScreenIT
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THE EMOTIONAL IMPACT OF THE ASRM GUIDELINES ON FERTILITY PATIENTS DURING THE COVID-19 PANDEMIC
This article has 6 authors:Reviewed by ScreenIT
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Achieving herd immunity against COVID-19 at the country level by the exit strategy of a phased lift of control
This article has 2 authors:Reviewed by ScreenIT
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Predicting mortality risk in patients with COVID-19 using machine learning to help medical decision-making
This article has 2 authors:Reviewed by ScreenIT
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Estimating the Risk of COVID-19 Death during the Course of the Outbreak in Korea, February–May 2020
This article has 4 authors:Reviewed by ScreenIT
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Computational Prediction of the Comprehensive SARS-CoV-2 vs. Human Interactome to Guide the Design of Therapeutics
This article has 3 authors:Reviewed by ScreenIT
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Sequence analysis of SARS-CoV-2 genome reveals features important for vaccine design
This article has 9 authors:Reviewed by ScreenIT
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Two linear epitopes on the SARS-CoV-2 spike protein that elicit neutralising antibodies in COVID-19 patients
This article has 23 authors:Reviewed by ScreenIT
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Identification of Human Single-Domain Antibodies against SARS-CoV-2
This article has 14 authors:Reviewed by ScreenIT
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Susceptibility of ferrets, cats, dogs, and other domesticated animals to SARS–coronavirus 2
This article has 21 authors:Reviewed by ScreenIT