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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Modelling the active SARS-CoV-2 helicase complex as a basis for structure-based inhibitor design
This article has 10 authors:Reviewed by ScreenIT
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The implementation of remote home monitoring models during the COVID-19 pandemic in England
This article has 9 authors:Reviewed by ScreenIT
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UV light dosage distribution over irregular respirator surfaces. Methods and implications for safety
This article has 6 authors:Reviewed by ScreenIT
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Comparison of SARS-CoV-2 Exit Strategies Building Blocks
This article has 3 authors:Reviewed by ScreenIT
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Evaluating the impact of non-pharmaceutical interventions for SARS-CoV-2 on a global scale
This article has 9 authors:Reviewed by ScreenIT
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Interleukin-6 Receptor Antagonists in Critically Ill Patients with Covid-19 – Preliminary report
This article has 63 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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Estimated surge in hospital and intensive care admission because of the coronavirus disease 2019 pandemic in the Greater Toronto Area, Canada: a mathematical modelling study
This article has 16 authors:Reviewed by ScreenIT
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Lung Ultrasound Findings in Patients Hospitalized With COVID‐19
This article has 11 authors:Reviewed by ScreenIT
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Comparative evaluation of 19 reverse transcription loop-mediated isothermal amplification assays for detection of SARS-CoV-2
This article has 10 authors:Reviewed by ScreenIT
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Face-Masking, an Acceptable Protective Measure against COVID-19 in Ugandan High-Risk Groups
This article has 4 authors:Reviewed by ScreenIT