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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COVID-19 Diagnosis based on Taste Disorders: A Case-Control Study
This article has 12 authors:Reviewed by ScreenIT
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Evaluation of symptomatic patient saliva as a sample type for the Abbott ID NOW COVID-19 assay
This article has 10 authors:Reviewed by ScreenIT
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Evaluating the adequacy of Prima Covid-19 IgG/IgM Rapid Test for the assessment of exposure to SARS-CoV-2 virus
This article has 5 authors:Reviewed by ScreenIT
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The chest CT features of coronavirus disease 2019 (COVID-19) in China: a meta-analysis of 19 retrospective studies
This article has 5 authors:Reviewed by ScreenIT
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Genetic variants of PIEZO1 associate with COVID-19 fatality
This article has 7 authors:Reviewed by ScreenIT
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When “Shelter-in-Place” Isn’t Shelter That’s Safe: a Rapid Analysis of Domestic Violence Case Differences during the COVID-19 Pandemic and Stay-at-Home Orders
This article has 1 author:Reviewed by ScreenIT
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Prevalence, clinical characteristics and treatment outcomes of HIV and SARS-CoV-2 co-infection: a systematic review and meta-analysis
This article has 7 authors:Reviewed by ScreenIT
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It’s the very time to learn a pandemic lesson: why have predictive techniques been ineffective when describing long-term events?
This article has 2 authors:Reviewed by ScreenIT
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Spreading of COVID-19 in Brazil: Impacts and uncertainties in social distancing strategies
This article has 7 authors:Reviewed by ScreenIT
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Testing for tracing or testing just for treating? A comparative analysis of strategies to face COVID-19 pandemic
This article has 1 author:Reviewed by ScreenIT