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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Vulnerability to rumours during the COVID-19 pandemic in Singapore
This article has 4 authors:Reviewed by ScreenIT
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Forecasting the cumulative number of COVID-19 deaths in China: a Boltzmann function-based modeling study
This article has 6 authors:Reviewed by ScreenIT
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Association between COVID-19 outcomes and mask mandates, adherence, and attitudes
This article has 9 authors:Reviewed by ScreenIT
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What is the value of community oximetry monitoring in people with SARS-CoV-2? – A prospective, open-label clinical study
This article has 3 authors:Reviewed by ScreenIT
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Kidney injury molecule-1 is a potential receptor for SARS-CoV-2
This article has 12 authors:Reviewed by ScreenIT
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Kinetics and correlates of the neutralizing antibody response to SARS-CoV-2
This article has 24 authors:Reviewed by ScreenIT
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Prevalence of SARS-CoV-2 IgG antibodies and their association with clinical symptoms of COVID-19 in Estonia (KoroSero-EST-1 study)
This article has 19 authors:Reviewed by ScreenIT
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Clinical and Virological Characteristics of Hospitalized COVID-19 Patients in a German Tertiary Care Center during the First Wave of the SARS-CoV-2 Pandemic
This article has 30 authors:Reviewed by ScreenIT
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Cryo-EM and antisense targeting of the 28-kDa frameshift stimulation element from the SARS-CoV-2 RNA genome
This article has 19 authors:Reviewed by ScreenIT
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Environmental and climatic impact on the infection and mortality of SARS-CoV-2 in Peru
This article has 4 authors:Reviewed by ScreenIT