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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Association Between the Physical Work Environment and Work Functioning Impairment While Working From Home Under the COVID-19 Pandemic in Japanese Workers
This article has 9 authors:Reviewed by ScreenIT
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Genetic associations with severe COVID-19
This article has 3 authors:Reviewed by ScreenIT
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Piecewise Isothermal Nucleic Acid Testing (PINAT) for Infectious Disease Detection with Sample-to-Result Integration at the Point-of-Care
This article has 17 authors:Reviewed by ScreenIT
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Genome sequencing and analysis of an emergent SARS-CoV-2 variant characterized by multiple spike protein mutations detected from the Central Visayas Region of the Philippines
This article has 32 authors:Reviewed by ScreenIT
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D614G mutation of SARS-CoV-2 spike protein enhances viral infectivity
This article has 12 authors:Reviewed by ScreenIT
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A Rapid Review of COVID-19 Vaccine Prioritization in the U.S.: Alignment between Federal Guidance and State Practice
This article has 3 authors:Reviewed by ScreenIT
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Engineered ACE2 receptor traps potently neutralize SARS-CoV-2
This article has 20 authors:Reviewed by ScreenIT
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A combination of cross-neutralizing antibodies synergizes to prevent SARS-CoV-2 and SARS-CoV pseudovirus infection
This article has 20 authors:Reviewed by ScreenIT
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Engineered disulfide reveals structural dynamics of locked SARS-CoV-2 spike
This article has 14 authors:Reviewed by ScreenIT
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The ORF8 protein of SARS-CoV-2 mediates immune evasion through down-regulating MHC-Ι
This article has 24 authors:Reviewed by ScreenIT