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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Is climate a curse or a bless in the Covid-19 virus fighting?
This article has 3 authors:Reviewed by ScreenIT
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Accessible LAMP-Enabled Rapid Test (ALERT) for Detecting SARS-CoV-2
This article has 12 authors:Reviewed by ScreenIT
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Mitigation Interventions in the United States: An Exploratory Investigation of Determinants and Impacts
This article has 6 authors:Reviewed by ScreenIT
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Diagnostic Performance of Pooled RT-PCR Testing for SARS-CoV-2 Detection
This article has 4 authors:Reviewed by ScreenIT
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A retrospective analysis of the dynamic transmission routes of the COVID-19 in mainland China
This article has 3 authors:Reviewed by ScreenIT
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Reproduction ratio and growth rates: Measures for an unfolding pandemic
This article has 3 authors:Reviewed by ScreenIT
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Impact of COVID-19 lockdown on psychosocial factors, health, and lifestyle in Scottish octogenarians: The Lothian Birth Cohort 1936 study
This article has 9 authors:Reviewed by ScreenIT
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The Uncertain COVID-19 Spread Pattern in India:
This article has 1 author:Reviewed by ScreenIT
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Human Pluripotent Stem Cell-Derived Neural Cells and Brain Organoids Reveal SARS-CoV-2 Neurotropism
This article has 16 authors:Reviewed by ScreenIT
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A rapid and sensitive method to detect SARS-CoV-2 virus using targeted-mass spectrometry
This article has 27 authors:Reviewed by ScreenIT