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: a crash test for biomedical publishing?
This article has 3 authors:Reviewed by ScreenIT
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Spreading Analysis of COVID-19 Epidemic in Bangladesh by Dynamical Mathematical Modelling
This article has 3 authors:Reviewed by ScreenIT
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A systematic review protocol of the antiviral activity of chloroquine and hydroxychloroquine against COVID-19
This article has 4 authors:Reviewed by ScreenIT
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Guillain-Barr é syndrome in COVID-19: A scoping review
This article has 2 authors:Reviewed by ScreenIT
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What triggers online help-seeking retransmission during the COVID-19 period? Empirical evidence from Chinese social media
This article has 4 authors:Reviewed by ScreenIT
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SARS Coronavirus-2 variant tracing within the first Coronavirus Disease 19 clusters in northern Germany
This article has 17 authors:Reviewed by ScreenIT
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Changes in mental health symptoms from pre-COVID-19 to COVID-19 among participants with systemic sclerosis from four countries: A Scleroderma Patient-centered Intervention Network (SPIN) Cohort study
This article has 101 authors:Reviewed by ScreenIT
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Risk factors and protective factors of mental health during COVID-19 outbreak and lockdown in adult Indian population- A cross-sectional study
This article has 3 authors:Reviewed by ScreenIT
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Longitudinal immune profiling reveals key myeloid signatures associated with COVID-19
This article has 20 authors:Reviewed by ScreenIT
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Array-based analysis of SARS-CoV-2, other coronaviruses, and influenza antibodies in convalescent COVID-19 patients
This article has 11 authors:Reviewed by ScreenIT