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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The infinite alleles model revisited: a Gibbs sampling approach
This article has 1 author:Reviewed by ScreenIT
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Blockade of interleukin seventeen (IL-17A) with secukinumab in hospitalized COVID-19 patients – the BISHOP study
This article has 16 authors:Reviewed by ScreenIT
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Association between the COVID-19 pandemic and pertussis derived from multiple nationwide data sources, France, 2013 to 2020
This article has 16 authors:Reviewed by ScreenIT
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CCEDRRN COVID-19 Infection Score (CCIS): development and validation in a Canadian cohort of a clinical risk score to predict SARS-CoV-2 infection in patients presenting to the emergency department with suspected COVID-19
This article has 17 authors:Reviewed by ScreenIT
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Self-protective behavioural responses to fomite-transmitted disease threats
This article has 4 authors:Reviewed by ScreenIT
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The incidence and in-hospital mortality of COVID-19 patients post-vaccination in eastern India
This article has 10 authors:Reviewed by ScreenIT
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Dique Filipeia: A rehabilitation protocol for non-intubated COVID-19 in-hospital patients
This article has 9 authors:Reviewed by ScreenIT
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A Quest for the Origin of the Uneven Spread of Covid-19 Cases
This article has 2 authors:Reviewed by ScreenIT
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Rosin Soap Exhibits Virucidal Activity
This article has 7 authors:Reviewed by ScreenIT
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Understanding Adverse Population Sentiment Towards the Spread of COVID-19 in the United States
This article has 5 authors:Reviewed by ScreenIT