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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Determinants of epidemic size and the impacts of lulls in seasonal influenza virus circulation
This article has 23 authors:Reviewed by ScreenIT
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Using multiple sampling strategies to estimate SARS-CoV-2 epidemiological parameters from genomic sequencing data
This article has 3 authors:Reviewed by ScreenIT
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SARS-CoV-2 Omicron Symptomatic Infections in Previously Infected or Vaccinated South African Healthcare Workers
This article has 7 authors:Reviewed by ScreenIT
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Comparative immunogenicity and safety of Gam-COVID-Vac and Sinopharm BBIBP-CorV vaccines: results of a pilot clinical study
This article has 5 authors:Reviewed by ScreenIT
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USA Winter 2021 CoVID-19 Resurgence Post-Christmas Update
This article has 1 author:Reviewed by ScreenIT
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The usefulness of D-dimer as a predictive marker for mortality in patients with COVID-19 hospitalized during the first wave in Italy
This article has 17 authors:Reviewed by ScreenIT
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A scalable pipeline for SARS-CoV-2 replicon construction based on de-novo synthesis
This article has 7 authors:Reviewed by ScreenIT
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Wastewater Surveillance of U.S. Coast Guard Installations and Seagoing Military Vessels to Mitigate the Risk of COVID-19 Outbreaks
This article has 20 authors:Reviewed by ScreenIT
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Circulatory exosomes from COVID-19 patients trigger NLRP3 inflammasome in endothelial cells
This article has 5 authors:Reviewed by ScreenIT
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Primary macrophages exhibit a modest inflammatory response early in SARS-CoV-2 infection
This article has 4 authors:Reviewed by ScreenIT