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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Nucleotide Analogues as Inhibitors of Viral Polymerases
This article has 5 authors:Reviewed by ScreenIT
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Head-to-head comparison of direct-input RT-PCR and RT-LAMP against RT-qPCR on extracted RNA for rapid SARS-CoV-2 diagnostics
This article has 17 authors:Reviewed by ScreenIT
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Antecedent use of renin-angiotensin system inhibitors is associated with reduced mortality in elderly hypertensive Covid-19 patients
This article has 21 authors:Reviewed by ScreenIT
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SARS-CoV-2 transmission and control in a hospital setting: an individual-based modelling study
This article has 10 authors:Reviewed by ScreenIT
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Modeling the COVID-19 epidemic in Okinawa
This article has 4 authors:Reviewed by ScreenIT
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Prevalence of IgG antibodies against the severe acute respiratory syndrome coronavirus-2 among healthcare workers in Tennessee during May and June, 2020
This article has 14 authors:Reviewed by ScreenIT
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Discovery of Cyclic Peptide Ligands to the SARS-CoV-2 Spike Protein Using mRNA Display
This article has 16 authors:Reviewed by ScreenIT
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Hospital-Based Contact Tracing of Patients With COVID-19 and Health Care Workers During the COVID-19 Pandemic in Eastern India: Cross-sectional Study
This article has 18 authors:Reviewed by ScreenIT
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Untuned antiviral immunity in COVID-19 revealed by temporal type I/III interferon patterns and flu comparison
This article has 16 authors:Reviewed by ScreenIT
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Red blood cells injuries and hypersegmented neutrophils in COVID-19 peripheral blood film
This article has 11 authors:Reviewed by ScreenIT