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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Microbial signatures in the lower airways of mechanically ventilated COVID-19 patients associated with poor clinical outcome
This article has 52 authors:Reviewed by ScreenIT
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Insights into Cross-species Evolution of Novel Human Coronavirus SARS-CoV-2 and Defining Immune Determinants for Vaccine Development
This article has 2 authors:Reviewed by ScreenIT
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Convergence of Comorbidity and COVID-19 Infection to Fatality: An investigation based on health assessment and vaccination among older adults in Kerala, India
This article has 3 authors:Reviewed by ScreenIT
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AI for radiographic COVID-19 detection selects shortcuts over signal
This article has 3 authors:Reviewed by ScreenIT
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Available COVID-19 serial seroconversion panel for validation of SARS-CoV-2 antibody assays.
This article has 5 authors:Reviewed by ScreenIT
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Abrupt increase in the UK coronavirus death-case ratio in December 2020
This article has 2 authors:Reviewed by ScreenIT
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Healthcare personnel knowledge, motivations, concerns and intentions regarding COVID-19 vaccines: a cross-sectional survey
This article has 26 authors:Reviewed by ScreenIT
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50 policies, 1 pandemic, 500,000 deaths: Associations between state-level COVID-19 testing recommendations, tests per capita , undercounted deaths, vaccination policies, and doses per capita in the United States
This article has 2 authors:Reviewed by ScreenIT
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Modeling the Spring 2020 New York City COVID-19 Epidemic: New Criteria and Methods for Prediction
This article has 2 authors:Reviewed by ScreenIT
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Preliminary estimation of the novel coronavirus disease (COVID-19) cases in Iran: A modelling analysis based on overseas cases and air travel data
This article has 7 authors:Reviewed by ScreenIT