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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Favipiravir treatment does not influence disease progression among adult patients hospitalized with moderate-to-severe COVID-19: a prospective, sequential cohort study from Hungary
This article has 9 authors:Reviewed by ScreenIT
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Vaccination in a two-group epidemic model
This article has 4 authors:Reviewed by ScreenIT
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Handyfuge-LAMP: low-cost and electricity-free centrifugation for isothermal SARS-CoV-2 detection in saliva
This article has 4 authors:Reviewed by ScreenIT
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Association of HLA Class I Genotypes With Severity of Coronavirus Disease-19
This article has 7 authors:Reviewed by ScreenIT
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What predicts adherence to COVID-19 government guidelines? Longitudinal analyses of 51,000 UK adults
This article has 3 authors:Reviewed by ScreenIT
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Lack of consideration of sex and gender in COVID-19 clinical studies
This article has 4 authors:Reviewed by ScreenIT
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Novel SARS-CoV-2 spike variant identified through viral genome sequencing of the pediatric Washington D.C. COVID-19 outbreak
This article has 14 authors:Reviewed by ScreenIT
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On the heterogeneity of infections, containment measures and the preliminary forecast of COVID-19 epidemic
This article has 4 authors:Reviewed by ScreenIT
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Water, Sanitation, and Hygiene Practices and Challenges during the COVID-19 Pandemic: A Cross-Sectional Study in Rural Odisha, India
This article has 6 authors:Reviewed by ScreenIT
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Early Identification of SARS-CoV-2 Emergence in the DoD via Retrospective Analysis of 2019-2020 Upper Respiratory Illness Samples
This article has 13 authors:Reviewed by ScreenIT