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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Re-emergence of COVID-19 in Beijing was triggered by frozen virus: evidence from molecular clock
This article has 7 authors:Reviewed by ScreenIT
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Previous COVID-19 infection, but not Long-COVID, is associated with increased adverse events following BNT162b2/Pfizer vaccination
This article has 5 authors:Reviewed by ScreenIT
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SARS-CoV-2 Bearing a Mutation at the S1/S2 Cleavage Site Exhibits Attenuated Virulence and Confers Protective Immunity
This article has 13 authors:Reviewed by ScreenIT
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Investigation of the ventilation situation in a lecture room of building 033 at the Universität der Bundeswehr München
This article has 3 authors:Reviewed by ScreenIT
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A global database of COVID-19 vaccinations
This article has 8 authors:Reviewed by ScreenIT
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Single-cell sequencing of plasma cells from COVID-19 patients reveals highly expanded clonal lineages produce specific and neutralizing antibodies to SARS-CoV-2
This article has 18 authors:Reviewed by ScreenIT
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Optimal mobility restriction minimizing COVID-19 and excess suicide deaths in Japan
This article has 4 authors:Reviewed by ScreenIT
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Pediatric COVID-19 patients in South Brazil show abundant viral mRNA and strong specific anti-viral responses
This article has 31 authors:Reviewed by ScreenIT
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Impact of the COVID-19 pandemic on the surveillance, prevention and control of antimicrobial resistance: a global survey
This article has 18 authors:Reviewed by ScreenIT
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Adjuvanting a subunit SARS-CoV-2 nanoparticle vaccine to induce protective immunity in non-human primates
This article has 60 authors:Reviewed by ScreenIT