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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A Model Predicting Mortality of Hospitalized Covid-19 Patients Four Days After Admission: Development, Internal and Temporal-External Validation
This article has 30 authors:Reviewed by ScreenIT
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A dynamic regulatory interface on SARS-CoV-2 RNA polymerase
This article has 8 authors:Reviewed by ScreenIT
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COVID-19 PANDEMICS: HOW FAR ARE WE FROM HERD IMMUNITY?
This article has 3 authors:Reviewed by ScreenIT
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Predictions of Covid-19 Related Unemployment On Suicide and All-cause Mortality
This article has 1 author:Reviewed by ScreenIT
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Natural history, trajectory, and management of mechanically ventilated COVID-19 patients in the United Kingdom
This article has 21 authors:Reviewed by ScreenIT
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Mental health and wellbeing among people with informal caring responsibilities across different time points during the COVID-19 pandemic: a population-based propensity score matching analysis
This article has 3 authors:Reviewed by ScreenIT
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Logistic Approach to COVID - 19 Epidemic Evolution in Brazil
This article has 2 authors:Reviewed by ScreenIT
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Rigid monoclonal antibodies improve detection of SARS-CoV-2 nucleocapsid protein
This article has 6 authors:Reviewed by ScreenIT
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Early detection and surveillance of SARS-CoV-2 genomic variants in wastewater using COJAC
This article has 24 authors:Reviewed by ScreenIT
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Women in power: Female leadership and public health outcomes during the COVID-19 pandemic
This article has 12 authors:Reviewed by ScreenIT