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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Priority Setting of Ventilators in the COVID-19 Pandemic from the Public’s Perspective
This article has 3 authors:Reviewed by ScreenIT
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Resource requirements for reintroducing elective surgery during the COVID-19 pandemic: modelling study
This article has 10 authors:Reviewed by ScreenIT
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Identifying and Ranking Common COVID-19 Symptoms From Tweets in Arabic: Content Analysis
This article has 4 authors:Reviewed by ScreenIT
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Serial interval distribution of SARS-CoV-2 infection in Brazil
This article has 13 authors:Reviewed by ScreenIT
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Private Health Sector in India-Ready and Willing, Yet Underutilized in the Covid-19 Pandemic: A Cross-Sectional Study
This article has 10 authors:Reviewed by ScreenIT
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Multimorbidity, polypharmacy, and COVID-19 infection within the UK Biobank cohort
This article has 15 authors:Reviewed by ScreenIT
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A systematic review on the levels of antibodies in COVID-19 virus exposed but negative newborns: a possible vertical transmission of IgG/ IgM
This article has 2 authors:Reviewed by ScreenIT
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On the interplay between mobility and hospitalization capacity during the COVID-19 pandemic: The SEIRHUD model
This article has 9 authors:Reviewed by ScreenIT
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Renin–angiotensin system blockers and susceptibility to COVID-19: an international, open science, cohort analysis
This article has 33 authors:Reviewed by ScreenIT
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Chemoprophylaxis of COVID-19 with hydroxychloroquine - a study of health care workers attitude, adherence to regime and side effects
This article has 10 authors:Reviewed by ScreenIT