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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Hydroxychloroquine (HCQ) decreases the benefit of anti-PD-1 immune checkpoint blockade in tumor immunotherapy
This article has 8 authors:Reviewed by ScreenIT
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Credible learning of hydroxychloroquine and dexamethasone effects on COVID-19 mortality outside of randomized trials
This article has 6 authors:Reviewed by ScreenIT
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Analysis of COVID-19 cases and associated ventilator requirement in Indian States
This article has 5 authors:Reviewed by ScreenIT
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HIV status alters disease severity and immune cell responses in Beta variant SARS-CoV-2 infection wave
This article has 45 authors:This article has been curated by 1 group: -
Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7
This article has 7 authors:Reviewed by ScreenIT
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High prevalence of food insecurity, the adverse impact of COVID-19 in Brazilian favela
This article has 6 authors:Reviewed by ScreenIT
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On Reliability of the COVID-19 Forecasts
This article has 1 author:Reviewed by ScreenIT
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Low-Avidity CD4+ T Cell Responses to SARS-CoV-2 in Unexposed Individuals and Humans with Severe COVID-19
This article has 27 authors:Reviewed by ScreenIT
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Risk factors associated with morbidity and mortality outcomes of COVID-19 patients on the 14 th and 28 th day of the disease course: a retrospective cohort study in Bangladesh
This article has 10 authors:Reviewed by ScreenIT
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Patient characteristics and predictors of mortality in 470 adults admitted to a district general hospital in England with Covid-19
This article has 13 authors:Reviewed by ScreenIT