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 pandemic policy monitor (COV-PPM) - European level tracking data of non-pharmaceutical interventions
This article has 9 authors:Reviewed by ScreenIT
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Telecommuting Frequency and Preference among Japanese Workers According to Regional Cumulative COVID-19 Incidence: A Cross-Sectional Study
This article has 10 authors:Reviewed by ScreenIT
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Detection of SARS-CoV-2 in saliva using tailed amplicon sequencing
This article has 4 authors:Reviewed by ScreenIT
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Role of ATP in the RNA Translocation Mechanism of SARS-CoV-2 NSP13 Helicase
This article has 2 authors:Reviewed by ScreenIT
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Neutrophils cause critical illness in COVID-19 and reveal CDK6 inhibitors as potential treatment
This article has 8 authors: -
Fluorescence signatures of SARS-CoV-2 spike S1 proteins and a human ACE-2: excitation-emission maps and fluorescence lifetimes
This article has 7 authors:Reviewed by ScreenIT
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An AAV-ie based Vaccine effectively protects against SARS-CoV-2 and Circulating Variants
This article has 7 authors:Reviewed by ScreenIT
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Predictors of severe illness in children with multisystem inflammatory syndrome after SARS-CoV-2 infection: a multicentre cohort study
This article has 39 authors:Reviewed by ScreenIT
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Emergence and spread of the potential variant of interest (VOI) B.1.1.519 of SARS-CoV-2 predominantly present in Mexico
This article has 36 authors:Reviewed by ScreenIT
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Novel deterministic epidemic model considering mass vaccination and lockdown against coronavirus disease 2019 spread in Israel: A numerical study
This article has 3 authors:Reviewed by ScreenIT