ScreenIT
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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COVID-19 among people experiencing homelessness in England: a modelling study
This article has 8 authors:Reviewed by ScreenIT
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Assessing the impact of non-pharmaceutical interventions on SARS-CoV-2 transmission in Switzerland
This article has 5 authors:Reviewed by ScreenIT
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Safe Blues: The case for virtual safe virus spread in the long-term fight against epidemics
This article has 9 authors:Reviewed by ScreenIT
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Environmental Sampling for Severe Acute Respiratory Syndrome Coronavirus 2 During a COVID-19 Outbreak on the Diamond Princess Cruise Ship
This article has 29 authors:Reviewed by ScreenIT
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Social distancing and movement constraint as the most likely factors for COVID-19 outbreak control in Brazil
This article has 5 authors:Reviewed by ScreenIT
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Suppressing the impact of the COVID-19 pandemic using controlled testing and isolation
This article has 2 authors:Reviewed by ScreenIT
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Excess Mortality in the United States During the First Three Months of the COVID-19 Pandemic
This article has 3 authors:Reviewed by ScreenIT
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Risk of Secondary Infection Waves of COVID-19 in an Insular Region: The Case of the Balearic Islands, Spain
This article has 5 authors:Reviewed by ScreenIT
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Meta-analysis of diagnostic performance of serological tests for SARS-CoV-2 antibodies up to 25 April 2020 and public health implications
This article has 14 authors:Reviewed by ScreenIT
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Shared Antigen-specific CD8+ T cell Responses Against the SARS-COV-2 Spike Protein in HLA A*02:01 COVID-19 Participants
This article has 21 authors:Reviewed by ScreenIT