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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Are presymptomatic SARS-CoV-2 infections in nursing home residents unrecognised symptomatic infections? Sequence and metadata from weekly testing in an extensive nursing home outbreak
This article has 10 authors:Reviewed by ScreenIT
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A Saliva-Based RNA Extraction-Free Workflow Integrated With Cas13a for SARS-CoV-2 Detection
This article has 13 authors:Reviewed by ScreenIT
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Dynamic prioritization of COVID-19 vaccines when social distancing is limited for essential workers
This article has 3 authors:Reviewed by ScreenIT
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Harmonizing Heterogeneous Endpoints in Coronavirus Disease 2019 Trials Without Loss of Information
This article has 7 authors:Reviewed by ScreenIT
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A Bayesian framework for estimating the risk ratio of hospitalization for people with comorbidity infected by SARS-CoV-2 virus
This article has 2 authors:Reviewed by ScreenIT
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Association between consumption of fermented vegetables and COVID-19 mortality at a country level in Europe
This article has 12 authors:Reviewed by ScreenIT
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Experimental SARS-CoV-2 infection of bank voles - general susceptibility but lack of direct transmission
This article has 6 authors:Reviewed by ScreenIT
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Containment to outbreak tipping points in COVID-19
This article has 7 authors:Reviewed by ScreenIT
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Peginterferon Lambda-1a for treatment of outpatients with uncomplicated COVID-19: a randomized placebo-controlled trial
This article has 27 authors:Reviewed by ScreenIT
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Disease burden and clinical severity of the first pandemic wave of COVID-19 in Wuhan, China
This article has 12 authors:Reviewed by ScreenIT