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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Clinical effectiveness of convalescent plasma in hospitalized patients with COVID-19: a systematic review and meta-analysis
This article has 5 authors:Reviewed by ScreenIT
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How much leeway is there to relax COVID-19 control measures?
This article has 10 authors:Reviewed by ScreenIT
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SARS-CoV-2 outbreak in a tri-national urban area is dominated by a B.1 lineage variant linked to a mass gathering event
This article has 22 authors:Reviewed by ScreenIT
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Firearm purchasing and firearm violence during the coronavirus pandemic in the United States: a cross-sectional study
This article has 9 authors:Reviewed by ScreenIT, Rapid Reviews Infectious Diseases
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Potentials of constrained sliding mode control as an intervention guide to manage COVID19 spread
This article has 5 authors:Reviewed by ScreenIT
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Validation of an internationally derived patient severity phenotype to support COVID-19 analytics from electronic health record data
This article has 42 authors:Reviewed by ScreenIT
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SARS-CoV-2 genome analysis of strains in Pakistan reveals GH, S and L clade strains at the start of the pandemic
This article has 14 authors:Reviewed by ScreenIT
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SARS-Cov-2 Viral Load as an Indicator for COVID-19 Patients’ Hospital Stay
This article has 5 authors:Reviewed by ScreenIT
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Shorter androgen receptor polyQ alleles protect against life-threatening COVID-19 disease in European males
This article has 149 authors:Reviewed by ScreenIT
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Trends in Health Care Worker Intentions to Receive a COVID-19 Vaccine and Reasons for Hesitancy
This article has 3 authors:Reviewed by ScreenIT