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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Immunopathological signatures in multisystem inflammatory syndrome in children and pediatric COVID-19
This article has 90 authors:Reviewed by ScreenIT
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Effectiveness of COVID-19 vaccines against SARS-CoV-2 variants of concern: a systematic review and meta-analysis
This article has 5 authors:Reviewed by ScreenIT
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Assessing the impact of temperature and humidity exposures during early infection stages on case-fatality of COVID-19: A modelling study in Europe
This article has 2 authors:Reviewed by ScreenIT
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Lower probability and shorter duration of infections after COVID-19 vaccine correlate with anti-SARS-CoV-2 circulating IgGs
This article has 15 authors:Reviewed by ScreenIT
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The Report on China-Spain Joint Clinical Testing for Rapid COVID-19 Risk Screening by Eye-region Manifestations
This article has 22 authors:Reviewed by ScreenIT
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Non-pharmaceutical intervention levels to reduce the COVID-19 attack ratio among children
This article has 5 authors:Reviewed by ScreenIT
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SARS- CoV-2 viroporins: A multi-omics insight from nucleotides to amino acids
This article has 4 authors:Reviewed by ScreenIT
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SARS-CoV-2-Specific Antibody (Ab) Levels and the Kinetic of Ab Decline Determine Ab Persistence Over 1 Year
This article has 15 authors:Reviewed by ScreenIT
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Effect of Comorbidities on the Infection Rate and Severity of COVID-19: Nationwide Cohort Study With Propensity Score Matching
This article has 3 authors:Reviewed by ScreenIT
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Social Contacts and Transmission of COVID-19 in British Columbia, Canada
This article has 8 authors:Reviewed by ScreenIT