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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Detection and quantification of infectious severe acute respiratory coronavirus-2 in diverse clinical and environmental samples
This article has 13 authors:Reviewed by ScreenIT
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Broadly neutralizing antibodies to SARS-related viruses can be readily induced in rhesus macaques
This article has 38 authors:Reviewed by ScreenIT
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Host Cellular RNA Helicases Regulate SARS-CoV-2 Infection
This article has 1 author:Reviewed by ScreenIT
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A mouse-adapted SARS-CoV-2 strain replicating in standard laboratory mice
This article has 11 authors:Reviewed by ScreenIT
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Research Status of the Safety and Efficacy of Mesenchymal Stem Cells in the Treatment of COVID-19-Related Pneumonia: A Systematic Review and Meta-Analysis
This article has 7 authors:Reviewed by ScreenIT
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Efficacy and Safety of Andrographis Paniculata Extract in Patients with Mild COVID-19: A Randomized Controlled Trial
This article has 7 authors:Reviewed by ScreenIT
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Decoding clinical biomarker space of COVID-19: Exploring matrix factorization-based feature selection methods
This article has 22 authors:Reviewed by ScreenIT
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Using big data analytics to explore the relationship between government stringency and preventative social behaviour during the COVID-19 pandemic in the United Kingdom
This article has 9 authors:Reviewed by ScreenIT
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Application of nasal spray containing dimethyl sulfoxide (DMSO) and ethanol during the COVID-19 pandemic may protect healthcare workers: A randomized controlled trials
This article has 10 authors:Reviewed by ScreenIT
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Effectiveness of rosuvastatin plus colchicine, emtricitabine/tenofovir and combinations thereof in hospitalized patients with COVID-19: a pragmatic, open-label randomized trial
This article has 17 authors:Reviewed by ScreenIT