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 FDA-approved drug Alectinib compromises SARS-CoV-2 nucleocapsid phosphorylation and inhibits viral infection in vitro
This article has 45 authors:Reviewed by ScreenIT
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The Persistence of Vaccine Hesitancy: COVID-19 Vaccination Intention in New Zealand
This article has 1 author:Reviewed by ScreenIT
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Information given by websites selling home self-sampling COVID-19 tests: an analysis of accuracy and completeness
This article has 11 authors:Reviewed by ScreenIT
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Strict Lockdown versus Flexible Social Distance Strategy for COVID-19 Disease: a Cost-Effectiveness Analysis
This article has 2 authors:Reviewed by ScreenIT
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Evaluation of a novel community-based COVID-19 ‘Test-to-Care’ model for low-income populations
This article has 16 authors:Reviewed by ScreenIT
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Temporal association between human upper respiratory and gut bacterial microbiomes during the course of COVID-19 in adults
This article has 10 authors:Reviewed by ScreenIT
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Epidemiological Transition of Covid-19 in India from Higher to Lower HDI States and Territories: Implications for Prevention and Control
This article has 3 authors:Reviewed by ScreenIT
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Smoking, distress and COVID-19 in England: Cross-sectional population surveys from 2016 to 2020
This article has 6 authors:Reviewed by ScreenIT
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Socio-economic disparities and COVID-19 in the USA
This article has 3 authors:Reviewed by ScreenIT
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Characterization of cell-cell communication in COVID-19 patients
This article has 7 authors:Reviewed by ScreenIT