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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Rate of Angiotensin-Converting Enzyme Inhibitors and Angiotensin Receptor Blockers Use and the Number of COVID-19–Confirmed Cases and Deaths
This article has 4 authors:Reviewed by ScreenIT
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Psychosocial factors and hospitalisations for COVID-19: Prospective cohort study based on a community sample
This article has 6 authors:Reviewed by ScreenIT
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Delirium Incidence, Duration and Severity in Critically Ill Patients with COVID-19
This article has 4 authors:Reviewed by ScreenIT
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Characteristics and outcomes of COVID-19 patients in New York City’s public hospital system
This article has 29 authors:Reviewed by ScreenIT
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Evaluating the effect of demographic factors, socioeconomic factors, and risk aversion on mobility during the COVID-19 epidemic in France under lockdown: a population-based study
This article has 5 authors:Reviewed by ScreenIT
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Safety of Breastfeeding in Mothers with SARS-CoV-2 Infection
This article has 20 authors:Reviewed by ScreenIT
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Evaluation of COVID 19 infection in 279 cancer patients treated during a 90-day period in 2020 pandemic
This article has 1 author:Reviewed by ScreenIT
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SARS-CoV-2 infection: the environmental endurance of the virus can be influenced by the increase of temperature
This article has 12 authors:Reviewed by ScreenIT
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Improved and Simplified Diagnosis of Covid-19 using TE Extraction from Dry Swabs
This article has 7 authors:Reviewed by ScreenIT
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A Scalable Topical Vectored Vaccine Candidate Against SARS-CoV-2
This article has 2 authors:Reviewed by ScreenIT