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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Prothrombotic autoantibodies in serum from patients hospitalized with COVID-19
This article has 19 authors:Reviewed by ScreenIT
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Suppression of Groups Intermingling as an Appealing Option for Flattening and Delaying the Epidemiological Curve While Allowing Economic and Social Life at a Bearable Level during the COVID‐19 Pandemic
This article has 1 author:Reviewed by ScreenIT
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Development and validation of a simplified risk score for the prediction of critical COVID‐19 illness in newly diagnosed patients
This article has 18 authors:Reviewed by ScreenIT
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Contact tracing and isolation reduces covid-19 incidence in a structured agent-based model
This article has 2 authors:Reviewed by ScreenIT
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Viral surface geometry shapes influenza and coronavirus spike evolution through antibody pressure
This article has 1 author:Reviewed by ScreenIT
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Genetic and Phenotypic Evidence for the Causal Relationship Between Aging and COVID-19
This article has 7 authors:Reviewed by ScreenIT
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The unexpected dynamics of COVID-19 in Manaus, Brazil: Was herd immunity achieved?
This article has 6 authors:Reviewed by ScreenIT
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Can particulate matter be identified as the primary cause of the rapid spread of CoViD-19 in some areas of Northern Italy?
This article has 8 authors:Reviewed by ScreenIT
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SARS-CoV-2 escapes CD8 T cell surveillance via mutations in MHC-I restricted epitopes
This article has 26 authors:Reviewed by ScreenIT
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The Role of Hydroxychloroquine in COVID-19 Treatment: A Systematic Review and Meta-Analysis
This article has 18 authors:Reviewed by ScreenIT