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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SARS-CoV-2–associated ssRNAs activate inflammation and immunity via TLR7/8
This article has 17 authors:Reviewed by ScreenIT
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Disparities in excess deaths from the COVID-19 pandemic among migrant workers in Kuwait
This article has 5 authors:Reviewed by ScreenIT
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Substitutions and codon usage in SARS-CoV-2 in mammals indicate natural selection and host adaptation
This article has 9 authors:Reviewed by ScreenIT
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Inactivation of Human Coronavirus by Titania Nanoparticle Coatings and UVC Radiation: Throwing Light on SARS-CoV-2
This article has 5 authors:Reviewed by ScreenIT
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Fine-tuning the spike: role of the nature and topology of the glycan shield in the structure and dynamics of the SARS-CoV-2 S
This article has 6 authors:Reviewed by ScreenIT
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Returning to the Workplace During the COVID-19 Pandemic: The Concerns of Australian Workers
This article has 5 authors:Reviewed by ScreenIT
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Comparison of cough particle exposure for indoor commercial and aircraft cabin spaces
This article has 5 authors:Reviewed by ScreenIT
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Convergent antibody responses to SARS-CoV-2 in convalescent individuals
This article has 46 authors:Reviewed by ScreenIT
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Real-world Effect of Monoclonal Antibody Treatment in COVID-19 Patients in a Diverse Population in the United States
This article has 14 authors:Reviewed by ScreenIT
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De novo design of potent and resilient hACE2 decoys to neutralize SARS-CoV-2
This article has 35 authors:Reviewed by ScreenIT