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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COVID-19 in Brazilian children and adolescents: findings from 21 hospitals / COVID-19 em crianças e adolescentes brasileiros: registros de 21 hospitais
This article has 23 authors:Reviewed by ScreenIT
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Genomic analysis of SARS-CoV-2 variants of concern identified from the ChAdOx1 nCoV-19 immunized patients from Southwest part of Bangladesh
This article has 12 authors:Reviewed by ScreenIT
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Mixed invasive fungal infections among COVID-19 patients
This article has 9 authors:Reviewed by ScreenIT
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Diagnosing COVID-19 in human serum using Raman spectroscopy
This article has 6 authors:Reviewed by ScreenIT
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Severity of respiratory failure and computed chest tomography in acute COVID-19 correlates with pulmonary function and respiratory symptoms after infection with SARS-CoV-2: An observational longitudinal study over 12 months
This article has 19 authors:Reviewed by ScreenIT
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BNT162b2 and mRNA-1273 COVID-19 vaccine effectiveness against the SARS-CoV-2 Delta variant in Qatar
This article has 24 authors:Reviewed by ScreenIT
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ImputeCoVNet: 2D ResNet Autoencoder for Imputation of SARS-CoV-2 Sequences
This article has 5 authors:Reviewed by ScreenIT
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A diabetic milieu increases cellular susceptibility to SARS-CoV-2 infections in engineered human kidney organoids and diabetic patients
This article has 25 authors:Reviewed by ScreenIT
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Characterising the persistence of RT-PCR positivity and incidence in a community survey of SARS-CoV-2
This article has 22 authors:Reviewed by ScreenIT
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Use of healthcare services during the COVID-19 pandemic in urban Ethiopia: evidence from retrospective health facility survey data
This article has 5 authors:Reviewed by ScreenIT