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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Drug Repurposing Screen for Compounds Inhibiting the Cytopathic Effect of SARS-CoV-2
This article has 19 authors:Reviewed by ScreenIT
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Circulating Levels of Calcitonin Gene-Related Peptide Are Lower in COVID-19 Patients
This article has 10 authors:Reviewed by ScreenIT
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Genomic epidemiology of superspreading events in Austria reveals mutational dynamics and transmission properties of SARS-CoV-2
This article has 38 authors:Reviewed by ScreenIT
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Ongoing Recombination in SARS-CoV-2 Revealed through Genealogical Reconstruction
This article has 3 authors:Reviewed by ScreenIT
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Development of a Rapid and Sensitive CasRx-Based Diagnostic Assay for SARS-CoV-2
This article has 13 authors:Reviewed by ScreenIT
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COVID-19 Outbreak: Model-Driven Impact Analysis Comparing Oman and Pakistan
This article has 3 authors:Reviewed by ScreenIT
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Effect of RBD mutations in spike glycoprotein of SARS-CoV-2 on neutralizing IgG affinity
This article has 3 authors:Reviewed by ScreenIT
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Maternal mental health and coping during the COVID‐19 lockdown in the UK: Data from the COVID‐19 New Mum Study
This article has 5 authors:Reviewed by ScreenIT
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Causal associations between COVID-19 and atrial fibrillation: A bidirectional Mendelian randomization study
This article has 13 authors:Reviewed by ScreenIT
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From a recombinant key antigen to an accurate, affordable serological test: Lessons learnt from COVID-19 for future pandemics
This article has 18 authors:Reviewed by ScreenIT