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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Lessons learnt from the use of compartmental models over the COVID-19 induced lockdown in France
This article has 14 authors:Reviewed by ScreenIT
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Spread of COVID-19 in India: A Simple Algebraic Study
This article has 1 author:Reviewed by ScreenIT
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Accuracy of Samsung Smartphone Integrated Pulse Oximetry Meets Full FDA Clearance Standards for Clinical Use
This article has 3 authors:Reviewed by ScreenIT
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Analytical and clinical performances of five immunoassays for the detection of SARS-CoV-2 antibodies in comparison with neutralization activity
This article has 10 authors:Reviewed by ScreenIT
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Data presented by the UK government as lockdown was eased shows the transmission of COVID-19 had already increased
This article has 1 author:Reviewed by ScreenIT
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Sample-to-answer COVID-19 nucleic acid testing using a low-cost centrifugal microfluidic platform with bead-based signal enhancement and smartphone read-out
This article has 9 authors:Reviewed by ScreenIT
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Examining the effect of information channel on COVID-19 vaccine acceptance
This article has 8 authors:Reviewed by ScreenIT
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Resilient SARS-CoV-2 diagnostics workflows including viral heat inactivation
This article has 37 authors:Reviewed by ScreenIT
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Epidemiological and economic impact of COVID-19 in the US
This article has 12 authors:Reviewed by ScreenIT
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Assessing the risks of ‘infodemics’ in response to COVID-19 epidemics
This article has 5 authors:Reviewed by ScreenIT