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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Learnings from the Australian first few X household transmission project for COVID-19
This article has 7 authors:Reviewed by ScreenIT
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TNF-α+ CD4+ T cells dominate the SARS-CoV-2 specific T cell response in COVID-19 outpatients and are associated with durable antibodies
This article has 22 authors:Reviewed by ScreenIT
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Converting non-neutralizing SARS-CoV-2 antibodies targeting conserved epitopes into broad-spectrum inhibitors through receptor blockade
This article has 6 authors:Reviewed by ScreenIT
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Anti-SARS-CoV-2 Seropositivity Among Medical Students in Copenhagen
This article has 9 authors:Reviewed by ScreenIT
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SARS‐CoV‐2 re‐infection risk in Austria
This article has 8 authors:Reviewed by ScreenIT
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Performance characteristics of five antigen-detecting rapid diagnostic test (Ag-RDT) for SARS-CoV-2 asymptomatic infection: a head-to-head benchmark comparison
This article has 22 authors:Reviewed by ScreenIT
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Associations Between Measures of Social Distancing and Severe Acute Respiratory Syndrome Coronavirus 2 Seropositivity: A Nationwide Population-based Study in the Netherlands
This article has 11 authors:Reviewed by ScreenIT
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Effect of COVID-19 mRNA Vaccine on Human Lung Carcinoma Cells In Vitro by Means of Raman Spectroscopy and Imaging
This article has 2 authors:Reviewed by ScreenIT
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Template-based design of peptides to inhibit SARS-CoV-2 RNA-dependent RNA polymerase complexation
This article has 5 authors:Reviewed by ScreenIT
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Close relatives of MERS-CoV in bats use ACE2 as their functional receptors
This article has 23 authors:Reviewed by ScreenIT