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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A Comparative Study of Target Reconstruction of Ultra-High-Resolution CT for Patients with Corona-Virus Disease 2019 (COVID-19)
This article has 6 authors:Reviewed by ScreenIT
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Predictors of households at risk for food insecurity in the United States during the COVID-19 pandemic
This article has 7 authors:Reviewed by ScreenIT
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Assessing relative COVID-19 mortality: a Swiss population-based study
This article has 7 authors:Reviewed by ScreenIT
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Estimation of global case fatality rate of coronavirus disease 2019 (COVID-19) using meta-analyses: Comparison between calendar date and days since the outbreak of the first confirmed case
This article has 20 authors:Reviewed by ScreenIT
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How to Synchronize Longitudinal Patient Data With the Underlying Disease Progression: A Pilot Study Using the Biomarker CRP for Timing COVID-19
This article has 13 authors:Reviewed by ScreenIT
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Detection profile of SARS‐CoV‐2 using RT‐PCR in different types of clinical specimens: A systematic review and meta‐analysis
This article has 4 authors:Reviewed by ScreenIT
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Determinants of COVID-19 incidence and mortality: A cross-country analysis
This article has 9 authors:Reviewed by ScreenIT
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Coronavirus Disease 2019 (COVID-19): A Cross-Sectional Survey of the Knowledge, Attitudes, Practices (KAP) and Misconceptions in the General Population of Katsina State, Nigeria
This article has 14 authors:Reviewed by ScreenIT
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Estimating the impact of control measures to prevent outbreaks of COVID-19 associated with air travel into a COVID-19-free country
This article has 4 authors:Reviewed by ScreenIT
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The male excess case-fatality rates for COVID-19 – A meta-analytic study of the age-related differences and consistency over six countries
This article has 4 authors:Reviewed by ScreenIT