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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Artemisia annua L. extracts inhibit the in vitro replication of SARS-CoV-2 and two of its variants
This article has 7 authors:Reviewed by ScreenIT
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A patient satisfaction survey and educational package to improve the care of people hospitalised with COVID-19: an observational study, Liverpool, UK
This article has 13 authors:Reviewed by ScreenIT
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Recurrence of COVID-19 associated with reduced T-cell responses in a monozygotic twin pair
This article has 31 authors:Reviewed by ScreenIT
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Open Access and Altmetrics in the pandemic age: Forescast analysis on COVID-19 literature
This article has 3 authors:Reviewed by ScreenIT
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Multiplex SARS-CoV-2 Genotyping Reverse Transcriptase PCR for Population-Level Variant Screening and Epidemiologic Surveillance
This article has 14 authors:Reviewed by ScreenIT
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The SARS-CoV-2 Y453F mink variant displays a striking increase in ACE-2 affinity but does not challenge antibody neutralization
This article has 7 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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A protease-activatable luminescent biosensor and reporter cell line for authentic SARS-CoV-2 infection
This article has 16 authors:Reviewed by ScreenIT
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Mechanistic modeling of the SARS-CoV-2 and immune system interplay unravels design principles for diverse clinicopathological outcomes
This article has 4 authors:Reviewed by ScreenIT
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Effectiveness of various cleaning strategies in acute and long-term care facilities during novel corona virus 2019 disease pandemic-related staff shortages
This article has 11 authors:Reviewed by ScreenIT
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Molecular strategies for antibody binding and escape of SARS-CoV-2 and its mutations
This article has 3 authors:Reviewed by ScreenIT