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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Covid-19 transmission dynamics during the unlock phase and significance of testing
This article has 3 authors:Reviewed by ScreenIT
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COVID-19 mortality: positive correlation with cloudiness but no correlation with sunlight and latitude in Europe
This article has 3 authors:Reviewed by ScreenIT
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IGI-LuNER: single-well multiplexed RT-qPCR test for SARS-CoV-2
This article has 22 authors:Reviewed by ScreenIT
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Modeling the evolution of SARS-CoV-2 under non-pharmaceutical interventions and testing
This article has 3 authors:Reviewed by ScreenIT
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Prediction of Covid-19 Infections Through December 2020 for 10 US States Using a Two Parameter Transmission Model Incorporating Outdoor Temperature and School Re-Opening Effects
This article has 1 author:Reviewed by ScreenIT
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Clinical evaluation of a fully automated, laboratory-developed multiplex RT-PCR assay integrating dual-target SARS-CoV-2 and influenza A/B detection on a high-throughput platform
This article has 5 authors:Reviewed by ScreenIT
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Impacts of social and economic factors on the transmission of coronavirus disease 2019 (COVID-19) in China
This article has 3 authors:Reviewed by ScreenIT
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Modelling COVID-19 contagion: risk assessment and targeted mitigation policies
This article has 3 authors:Reviewed by ScreenIT
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A DNA intercalating dye-based RT-qPCR alternative to diagnose SARS-CoV-2
This article has 24 authors:Reviewed by ScreenIT
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COVID-19 containment on a college campus via wastewater-based epidemiology, targeted clinical testing and an intervention
This article has 12 authors:Reviewed by ScreenIT