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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Elevated Humoral Immune Response to SARS-CoV-2 at High Altitudes Revealed by an Anti-RBD “In-House” ELISA
This article has 23 authors:Reviewed by ScreenIT
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Nationwide rollout reveals efficacy of epidemic control through digital contact tracing
This article has 8 authors:Reviewed by ScreenIT
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D155Y substitution of SARS-CoV-2 ORF3a weakens binding with Caveolin-1
This article has 8 authors:Reviewed by ScreenIT
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Multi-ancestry fine mapping implicates OAS1 splicing in risk of severe COVID-19
This article has 14 authors:Reviewed by ScreenIT
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A national snapshot of U.S. adolescents' mental health and changing technology use during COVID-19
This article has 7 authors:Reviewed by ScreenIT
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Duration of Supplemental Oxygen Requirement and Predictors in Severe COVID-19 Patients in Ethiopia: A Survival Analysis
This article has 8 authors:Reviewed by ScreenIT
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Synonymous mutations and the molecular evolution of SARS-CoV-2 origins
This article has 3 authors:Reviewed by ScreenIT
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Alpha variant versus D614G strain in the Syrian hamster model
This article has 14 authors:Reviewed by ScreenIT
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A Real World Evaluation of the safety and immunogenicity of the Covishield vaccine, ChAdOx1 nCoV- 19 Corona Virus Vaccine (Recombinant) in Health Care Workers (HCW) in National Capital Region (NCR) of India: A preliminary report
This article has 14 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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Contribution of SARS-CoV-2 Accessory Proteins to Viral Pathogenicity in K18 Human ACE2 Transgenic Mice
This article has 17 authors:Reviewed by ScreenIT