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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Clinical characteristics of 50466 patients with 2019-nCoV infection
This article has 5 authors:Reviewed by ScreenIT
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A descriptive study of the impact of diseases control and prevention on the epidemics dynamics and clinical features of SARS-CoV-2 outbreak in Shanghai, lessons learned for metropolis epidemics prevention
This article has 28 authors:Reviewed by ScreenIT
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Serial Interval of COVID-19 among Publicly Reported Confirmed Cases
This article has 6 authors:Reviewed by ScreenIT
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Generalized anxiety disorder, depressive symptoms and sleep quality during COVID-19 outbreak in China: a web-based cross-sectional survey
This article has 2 authors:Reviewed by ScreenIT
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Comparison of throat swabs and sputum specimens for viral nucleic acid detection in 52 cases of novel coronavirus (SARS-Cov-2)-infected pneumonia (COVID-19)
This article has 6 authors:Reviewed by ScreenIT
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Early phylogenetic estimate of the effective reproduction number of SARS‐CoV‐2
This article has 5 authors:Reviewed by ScreenIT
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Development and evaluation of a rapid CRISPR-based diagnostic for COVID-19
This article has 15 authors: -
Estimating the asymptomatic proportion of coronavirus disease 2019 (COVID-19) cases on board the Diamond Princess cruise ship, Yokohama, Japan, 2020
This article has 4 authors:Reviewed by ScreenIT
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Efficacy of convalescent plasma for the treatment of severe influenza
This article has 10 authors:Reviewed by ScreenIT
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The cross-sectional study of hospitalized coronavirus disease 2019 patients in Xiangyang, Hubei province
This article has 14 authors:Reviewed by ScreenIT