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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Phylogenomics and Phylodynamics of SARS-CoV-2 Genomes Retrieved From India
This article has 6 authors:Reviewed by ScreenIT
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Timeline from receipt to online publication of COVID-19 original research articles
This article has 5 authors:Reviewed by ScreenIT
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A Cross-sectional Study of Immune Seroconversion to SARS-CoV-2 in Frontline Maternity Health Professionals
This article has 8 authors:Reviewed by ScreenIT
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COVID-19-associated ARDS treated with DEXamethasone (CoDEX): Study design and rationale for a randomized trial
This article has 19 authors:Reviewed by ScreenIT
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Analytical and Clinical Validation for RT-qPCR Detection of SARS-CoV-2 Without RNA Extraction
This article has 6 authors:Reviewed by ScreenIT
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A Metapopulation Network Model for the Spreading of SARS-CoV-2: Case Study for Ireland ⋆
This article has 6 authors:Reviewed by ScreenIT
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Hypoferremia is Associated With Increased Hospitalization and Oxygen Demand in COVID‐19 Patients
This article has 4 authors:Reviewed by ScreenIT
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SARS-CoV-2 has been circulating in northern Italy since December 2019: Evidence from environmental monitoring
This article has 8 authors:Reviewed by ScreenIT
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Evaluation on the diagnostic efficiency of different methods in detecting COVID-19
This article has 5 authors:Reviewed by ScreenIT
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Meningoencephalitis associated with COVID-19: a systematic review
This article has 7 authors:Reviewed by ScreenIT