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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Prioritization of Anti‐SARS‐Cov‐2 Drug Repurposing Opportunities Based on Plasma and Target Site Concentrations Derived from their Established Human Pharmacokinetics
This article has 22 authors:Reviewed by ScreenIT
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LONG-TERM CLINICAL OUTCOMES IN SURVIVORS OF CORONAVIRUS OUTBREAKS AFTER HOSPITALISATION OR ICU ADMISSION: A SYSTEMATIC REVIEW AND META-ANALYSIS OF FOLLOW-UP STUDIES
This article has 11 authors:Reviewed by ScreenIT
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Lessons from the Mainland of China’s Epidemic Experience in the First Phase about the Growth Rules of Infected and Recovered Cases of COVID-19 Worldwide
This article has 6 authors:Reviewed by ScreenIT
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Controlled Avalanche – A Regulated Voluntary Exposure Approach for Addressing Covid-19
This article has 6 authors:Reviewed by ScreenIT
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Global, regional, and national estimates of the population at increased risk of severe COVID-19 due to underlying health conditions in 2020: a modelling study
This article has 55 authors:Reviewed by ScreenIT
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Forecasting of COVID-19 Cases and Deaths Using ARIMA Models
This article has 2 authors:Reviewed by ScreenIT
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AI-driven quantification, staging and outcome prediction of COVID-19 pneumonia
This article has 35 authors:Reviewed by ScreenIT
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Spatial analysis of COVID-19 spread in Iran: Insights into geographical and structural transmission determinants at a province level
This article has 3 authors:Reviewed by ScreenIT
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The importance of timing of a population level intervention on COVID-19 mortality
This article has 3 authors:Reviewed by ScreenIT
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Characterization and clinical course of 1000 patients with coronavirus disease 2019 in New York: retrospective case series
This article has 48 authors:Reviewed by ScreenIT