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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Current RT-qPCR to detect SARS-CoV-2 may give positive results for related coronaviruses
This article has 4 authors:Reviewed by ScreenIT
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Gastrointestinal involvement attenuates COVID-19 severity and mortality
This article has 43 authors:Reviewed by ScreenIT
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MODELING COVID19 IN INDIA (Mar 3-May 7, 2020): HOW FLAT IS FLAT, AND OTHER HARD FACTS
This article has 1 author:Reviewed by ScreenIT
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Two original observations concerning bacterial infections in COVID-19 patients hospitalized in intensive care units during the first wave of the epidemic in France
This article has 13 authors:Reviewed by ScreenIT
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Profiling transcription factor sub-networks in type I interferon signaling and in response to SARS-CoV-2 infection
This article has 1 author:Reviewed by ScreenIT
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Phylo-geo-network and haplogroup analysis of 611 novel coronavirus (SARS-CoV-2) genomes from India
This article has 2 authors:Reviewed by ScreenIT
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PREDICTIONS FOR EUROPE FOR THE COVID-19 PANDEMIC AFTER LOCKDOWN WAS LIFTED USING AN SIR MODEL
This article has 1 author:Reviewed by ScreenIT
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Sample pooling, a population screening strategy for SARS-CoV2 to prevent future outbreak and mitigate the “second-wave” of infection of the virus
This article has 7 authors:Reviewed by ScreenIT
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Modeling the potential impact of indirect transmission on COVID-19 epidemic
This article has 6 authors:Reviewed by ScreenIT
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Throat wash as a source of SARS-CoV-2 RNA to monitor community spread of COVID-19
This article has 15 authors:Reviewed by ScreenIT