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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A syndromic surveillance tool to detect anomalous clusters of COVID-19 symptoms in the United States
This article has 11 authors:Reviewed by ScreenIT
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Mechanism of Ligand Recognition by Human ACE2 Receptor
This article has 3 authors:Reviewed by ScreenIT
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Efficacy of commercial mouth-rinses on SARS-CoV-2 viral load in saliva: randomized control trial in Singapore
This article has 12 authors:Reviewed by ScreenIT
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Bringing COVID-19 home for Christmas: a need for enhanced testing in healthcare institutions after the holidays
This article has 5 authors:Reviewed by ScreenIT
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Lockdown measures and their impact on single- and two-age-structured epidemic model for the COVID-19 outbreak in Mexico
This article has 7 authors:Reviewed by ScreenIT
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Long COVID Neuropsychological Deficits after Severe, Moderate, or Mild Infection
This article has 18 authors:Reviewed by ScreenIT
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EFFECT OF CONVALESCENT PLASMA ON MORTALITY IN PATIENTS WITH COVID-19 PNEUMONIA
This article has 11 authors:Reviewed by ScreenIT
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Effect of Screen time on Glycaemic control of Type 2 Diabetes patients during COVID-19 Outbreak: A Survey based Study
This article has 2 authors:Reviewed by ScreenIT
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Correlation of population mortality of COVID-19 and testing coverage: a comparison among 36 OECD countries
This article has 7 authors:Reviewed by ScreenIT
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SARS-CoV-2 Infection Depends on Cellular Heparan Sulfate and ACE2
This article has 36 authors:Reviewed by ScreenIT