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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On short-term trends and predictions for COVID-19 in France and the USA: comparison with Australia
This article has 5 authors:Reviewed by ScreenIT
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Contact tracing during Phase I of the COVID-19 pandemic in the Province of Trento, Italy: key findings and recommendations
This article has 7 authors: -
Mutational analysis and assessment of its impact on proteins of SARS-CoV-2 genomes from India
This article has 2 authors:Reviewed by ScreenIT
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COVID ‐19 Infection Prevention and Control Adherence in Long‐Term Care Facilities, Atlanta, Georgia
This article has 8 authors:Reviewed by ScreenIT
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Adenovirus and RNA-based COVID-19 vaccines’ perceptions and acceptance among healthcare workers in Saudi Arabia: a national survey
This article has 18 authors:Reviewed by ScreenIT
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Modelling palliative and end-of-life resource requirements during COVID-19: implications for quality care
This article has 7 authors:Reviewed by ScreenIT
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Microfluidic characterisation reveals broad range of SARS-CoV-2 antibody affinity in human plasma
This article has 19 authors:Reviewed by ScreenIT
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Relative disease burdens of COVID-19 and seasonal influenza in New York City, February 1 - April 18, 2020
This article has 2 authors:Reviewed by ScreenIT
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Antibody Status and Incidence of SARS-CoV-2 Infection in Health Care Workers
This article has 32 authors:Reviewed by ScreenIT
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Age-severity matched cytokine profiling reveals specific signatures in Covid-19 patients
This article has 12 authors:Reviewed by ScreenIT