ScreenIT
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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Delayed Recognition of Coronavirus Disease 2019 (COVID-19) in New York City: A Descriptive Analysis of COVID-19 Illness Prior to 29 February 2020
This article has 7 authors:Reviewed by ScreenIT
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Level and Duration of IgG and Neutralizing Antibodies to SARS-CoV-2 in Children with Symptomatic or Asymptomatic SARS-CoV-2 Infection
This article has 11 authors:Reviewed by ScreenIT
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Evaluation of machine learning for predicting COVID-19 outcomes from a national electronic medical records database
This article has 8 authors:Reviewed by ScreenIT
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The Omicron (B.1.1.529) SARS-CoV-2 variant of concern also affects companion animals
This article has 5 authors:Reviewed by ScreenIT
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SARS-CoV-2 Delta breakthrough infections in vaccinated patients
This article has 5 authors:Reviewed by ScreenIT
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Development of highly specific singleplex and multiplex real-time reverse transcription PCR assays for the identification of SARS-CoV-2 Omicron BA.1, BA.2 and Delta variants
This article has 5 authors:Reviewed by ScreenIT
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Markers of Fungal Translocation Are Elevated During Post-Acute Sequelae of SARS-CoV-2 Infection and Induce NF-κB Triggered Inflammation
This article has 29 authors:Reviewed by ScreenIT
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Anti-inflammatory therapy with nebulized dornase alfa for severe COVID-19 pneumonia: a randomized unblinded trial
This article has 25 authors:This article has been curated by 1 group:Reviewed by eLife, Rapid Reviews Infectious Diseases, ScreenIT
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Broadly neutralizing and protective nanobodies against diverse sarbecoviruses
This article has 22 authors:Reviewed by ScreenIT
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Epidemiology of Infections with SARS-CoV-2 Omicron BA.2 Variant, Hong Kong, January–March 2022
This article has 11 authors:Reviewed by ScreenIT