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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Challenges of deep learning methods for COVID-19 detection using public datasets
This article has 8 authors:Reviewed by ScreenIT
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A Novel Approach to Data Driven Pandemic Recovery: The Pandemic Recovery Acceleration Model
This article has 9 authors:Reviewed by ScreenIT
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Death Associated With Coronavirus (COVID-19) Infection in Individuals With Severe Mental Disorders in Sweden During the Early Months of the Outbreak—An Exploratory Cross-Sectional Analysis of a Population-Based Register Study
This article has 5 authors:Reviewed by ScreenIT
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The effectiveness of Non-pharmaceutical interventions in reducing the COVID-19 contagion in the UK, an observational and modelling study
This article has 4 authors:Reviewed by ScreenIT
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Real-time monitoring of COVID-19 dynamics using automated trend fitting and anomaly detection
This article has 17 authors:Reviewed by ScreenIT
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Heterogeneous mental health development during the COVID-19 pandemic in the United Kingdom
This article has 2 authors:Reviewed by ScreenIT
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Fully automated detection and differentiation of pandemic and endemic coronaviruses (NL63, 229E, HKU1, OC43 and SARS‐CoV‐2) on the hologic panther fusion
This article has 6 authors:Reviewed by ScreenIT
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Willingness to Vaccinate Against COVID-19 in the U.S.: Representative Longitudinal Evidence From April to October 2020
This article has 2 authors:Reviewed by ScreenIT
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A Bioluminescent Biosensor for Quantifying the Interaction of SARS-CoV-2 and Its Receptor ACE2 in Cells and In Vitro
This article has 9 authors:Reviewed by ScreenIT
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Development of a point-of-care test to detect SARS-CoV-2 from saliva which combines a simple RNA extraction method with colorimetric reverse transcription loop-mediated isothermal amplification detection
This article has 5 authors:Reviewed by ScreenIT