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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SARS-CoV-2 receptor networks in diabetic and COVID-19–associated kidney disease
This article has 32 authors:Reviewed by ScreenIT
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Effects of underlying morbidities on the occurrence of deaths in COVID-19 patients: A systematic review and meta-analysis
This article has 6 authors:Reviewed by ScreenIT
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ReScan, a Multiplex Diagnostic Pipeline, Pans Human Sera for SARS-CoV-2 Antigens
This article has 22 authors:Reviewed by ScreenIT
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The Early Food Insecurity Impacts of COVID-19
This article has 6 authors:Reviewed by ScreenIT
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A Continuously Active Antimicrobial Coating effective against Human Coronavirus 229E
This article has 4 authors:Reviewed by ScreenIT
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Modelling the Evolution of COVID-19 in High-Incidence European Countries and Regions: Estimated Number of Infections and Impact of Past and Future Intervention Measures
This article has 1 author:Reviewed by ScreenIT
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Studying the progress of COVID-19 outbreak in India using SIRD model
This article has 5 authors:Reviewed by ScreenIT
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Lifestyle risk factors, inflammatory mechanisms, and COVID-19 hospitalization: A community-based cohort study of 387,109 adults in UK
This article has 4 authors:Reviewed by ScreenIT
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This article has 11 authors:
Reviewed by ScreenIT
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Systemic hypoferremia and severity of hypoxemic respiratory failure in COVID-19
This article has 8 authors:Reviewed by ScreenIT