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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An Optimal Lockdown Relaxation Strategy for Minimizing the Economic Effects of COVID‐19 Outbreak
This article has 3 authors:Reviewed by ScreenIT
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An Alternative Binding Mode of IGHV3-53 Antibodies to the SARS-CoV-2 Receptor Binding Domain
This article has 13 authors:Reviewed by ScreenIT
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Ex vivo detection of SARS-CoV-2-specific CD8+ T cells: rapid induction, prolonged contraction, and formation of functional memory
This article has 32 authors:Reviewed by ScreenIT
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COVID-19 Spreading Dynamics in an Age-Structured Population with Selective Relaxation of Restrictions for Vaccinated Individuals : a Mathematical Modeling Study
This article has 3 authors:Reviewed by ScreenIT
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A simulation modelling toolkit for organising outpatient dialysis services during the COVID-19 pandemic
This article has 6 authors:Reviewed by ScreenIT
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The estimated impact of the COVID-19 epidemic in the general population of France
This article has 2 authors:Reviewed by ScreenIT
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N95 filtering face piece respirators remain effective after extensive reuse during the coronavirus disease 2019 (COVID-19) pandemic
This article has 12 authors:Reviewed by ScreenIT
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Logistic advantage of two-step screening strategy for SARS-CoV-2 at airport quarantine
This article has 3 authors:Reviewed by ScreenIT
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Treatment profiles and clinical outcomes of COVID-19 patients at private hospital in Jakarta
This article has 2 authors:Reviewed by ScreenIT
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COVID-19: Recovering estimates of the infected fatality rate during an ongoing pandemic through partial data
This article has 3 authors:Reviewed by ScreenIT