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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Immunoinformatic approach to design a vaccine against SARS-COV-2 membrane glycoprotein
This article has 7 authors:Reviewed by ScreenIT
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How Safe is Covishield (ChAdOx1nCoV-19) Vaccine? Experience from a Tertiary Care Hospital in South India
This article has 3 authors:Reviewed by ScreenIT
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Protein-sol pKa: prediction of electrostatic frustration, with application to coronaviruses
This article has 2 authors:Reviewed by ScreenIT
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The effect of population mobility on COVID-19 incidence in 314 Latin American cities: a longitudinal ecological study with mobile phone location data
This article has 9 authors:Reviewed by ScreenIT
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Quantitative SARS-CoV-2 Viral-Load Curves in Paired Saliva Samples and Nasal Swabs Inform Appropriate Respiratory Sampling Site and Analytical Test Sensitivity Required for Earliest Viral Detection
This article has 16 authors:Reviewed by ScreenIT
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Epidemiological and clinical insights from SARS-CoV-2 RT-PCR crossing threshold values, France, January to November 2020
This article has 29 authors:Reviewed by ScreenIT
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COVID-19 mortality in California based on death certificates: disproportionate impacts across racial/ethnic groups and nativity
This article has 5 authors:Reviewed by ScreenIT
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Wastewater surveillance-based city zonation for effective COVID-19 pandemic preparedness powered by early warning: A perspectives of temporal variations in SARS-CoV-2-RNA in Ahmedabad, India
This article has 5 authors:Reviewed by ScreenIT
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Proliferation of SARS-CoV-2 B.1.1.7 Variant in Pakistan-A Short Surveillance Account
This article has 7 authors:Reviewed by ScreenIT
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COVID-19 Pandemic Related Research in Africa: Bibliometric Analysis of Scholarly Output, Collaborations and Scientific Leadership
This article has 6 authors:Reviewed by ScreenIT