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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A comparison of persistence of SARS-CoV-2 variants on stainless steel
This article has 8 authors:Reviewed by ScreenIT
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Covid-19 does not look like what you are looking for: Clustering symptoms by nation and multi-morbidities reveal substantial differences to the classical symptom triad
This article has 5 authors:Reviewed by ScreenIT
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Ambroxol Hydrochloride Inhibits the Interaction between Severe Acute Respiratory Syndrome Coronavirus 2 Spike Protein’s Receptor Binding Domain and Recombinant Human ACE2
This article has 3 authors:Reviewed by ScreenIT
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SARS-CoV-2-Host Chimeric RNA-Sequencing Reads Do Not Necessarily Arise From Virus Integration Into the Host DNA
This article has 2 authors:Reviewed by ScreenIT
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Depression and anxiety symptoms in young adults before and during the COVID-19 pandemic: evidence from a Canadian population-based cohort
This article has 13 authors:Reviewed by ScreenIT
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Impaired Cytotoxic CD8 + T Cell Response in Elderly COVID-19 Patients
This article has 20 authors:Reviewed by ScreenIT
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Differential mutation profile of SARS-CoV-2 proteins across deceased and asymptomatic patients
This article has 2 authors:Reviewed by ScreenIT
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A tale of three SARS-CoV-2 variants with independently acquired P681H mutations in New York State
This article has 4 authors:Reviewed by ScreenIT
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Probability and estimated risk of SARS-CoV-2 transmission in the air travel system
This article has 7 authors:Reviewed by ScreenIT
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Occupational risk of COVID-19 by country of birth. A register-based study
This article has 2 authors:Reviewed by ScreenIT