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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Nelfinavir inhibits replication of severe acute respiratory syndrome coronavirus 2 in vitro
This article has 4 authors:Reviewed by ScreenIT
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LAMP-Seq: Population-Scale COVID-19 Diagnostics Using Combinatorial Barcoding
This article has 25 authors:Reviewed by ScreenIT
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A model to predict SARS‐CoV‐2 infection based on the first three‐month surveillance data in Brazil
This article has 6 authors:Reviewed by ScreenIT
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Decontamination of N95 masks for re-use employing 7 widely available sterilization methods
This article has 14 authors:Reviewed by ScreenIT
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Acute kidney injury in patients hospitalized with COVID-19 in Wuhan, China: A single-center retrospective observational study
This article has 10 authors:Reviewed by ScreenIT
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The impact of early social distancing at COVID-19 Outbreak in the largest Metropolitan Area of Brazil
This article has 8 authors:Reviewed by ScreenIT
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Noisy Pooled PCR for Virus Testing
This article has 3 authors:Reviewed by ScreenIT
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Genomic determinants of pathogenicity in SARS-CoV-2 and other human coronaviruses
This article has 6 authors:Reviewed by ScreenIT
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Optimize Clinical Laboratory Diagnosis of COVID-19 from Suspect Cases by Likelihood Ratio of SARS-CoV-2 IgM and IgG antibody
This article has 1 author:Reviewed by ScreenIT
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Interaction between malarial transmission and BCG vaccination with COVID-19 incidence in the world map: A cross-sectional study
This article has 3 authors:Reviewed by ScreenIT