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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Cholesterol Metabolism—Impacts on SARS-CoV-2 Infection Prognosis
This article has 19 authors:Reviewed by ScreenIT
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Projections for first-wave COVID-19 deaths across the US using social-distancing measures derived from mobile phones
This article has 9 authors:Reviewed by ScreenIT
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COVID-19 Outbreak Situations in Bangladesh: An Empirical Analysis
This article has 2 authors:Reviewed by ScreenIT
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Coronametrics: The UK turns the corner
This article has 2 authors:Reviewed by ScreenIT
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A Global Scale Estimate of Novel Coronavirus (COVID-19) Cases Using Extreme Value Distributions
This article has 6 authors:Reviewed by ScreenIT
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The current COVID-19 wave will likely be mitigated in the second-line European countries
This article has 6 authors:Reviewed by ScreenIT
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Self-Burnout – A New Path to the End of COVID-19
This article has 2 authors:Reviewed by ScreenIT
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America Addresses Two Epidemics – Cannabis and Coronavirus and their Interactions: An Ecological Geospatial Study
This article has 2 authors:Reviewed by ScreenIT
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Predicting the epidemic curve of the coronavirus (SARS-CoV-2) disease (COVID-19) using artificial intelligence: An application on the first and second waves
This article has 11 authors:Reviewed by ScreenIT
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Coronavirus disease (COVID-19) pandemic: an overview of systematic reviews
This article has 15 authors:Reviewed by ScreenIT