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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Development of a ferritin-based nanoparticle vaccine against the SARS-CoV-2 Omicron variant
This article has 10 authors:Reviewed by ScreenIT
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Broad Cross-Reactive IgA and IgG against Human Coronaviruses in Milk Induced by COVID-19 Vaccination and Infection
This article has 13 authors:Reviewed by ScreenIT
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Understanding adherence to self-isolation in the first phase of COVID-19 response
This article has 17 authors:Reviewed by ScreenIT
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Lower Risk of Multisystem Inflammatory Syndrome in Children With the Delta and Omicron Variants of Severe Acute Respiratory Syndrome Coronavirus 2
This article has 5 authors:Reviewed by ScreenIT
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Presence of Mediastinal Lymphadenopathy in Hospitalized Covid-19 Patients in a Tertiary Care Hospital in Pakistan – A cross-sectional study
This article has 3 authors:Reviewed by ScreenIT
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ACE2 gene expression and inflammatory conditions in periodontal microenvironment of COVID-19 patients with and without diabetes evaluated by qPCR
This article has 14 authors:Reviewed by ScreenIT
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Mechanistic and thermodynamic characterization of antivirals targeting druggable pocket of SARS-CoV-2 nucleocapsid
This article has 7 authors:Reviewed by ScreenIT
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C allele of rs479200 of the host EGLN1 gene - a risk factor for severe COVID-19 (pilot study)
This article has 12 authors:Reviewed by ScreenIT
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SARS-CoV-2 reinfections during the first three major COVID-19 waves in Bulgaria
This article has 4 authors:Reviewed by ScreenIT
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Unsupervised clustering reveals phenotypes of AKI in ICU COVID-19 patients
This article has 8 authors:Reviewed by ScreenIT