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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Country differences in hospitalisation, length of stay, admission to Intensive Care Units, and mortality due to SARS-CoV-2 infection at the end of the first wave in Europe: a rapid review of available literature
This article has 12 authors:Reviewed by ScreenIT
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COVID-19 pandemic control: balancing detection policy and lockdown intervention under ICU sustainability
This article has 4 authors:Reviewed by ScreenIT
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Loss of Taste and Smell as Distinguishing Symptoms of Coronavirus Disease 2019
This article has 15 authors:Reviewed by ScreenIT
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Derivation and validation of a prognostic model for predicting in-hospital mortality in patients admitted with COVID-19 in Wuhan, China: the PLANS (platelet lymphocyte age neutrophil sex) model
This article has 12 authors:Reviewed by ScreenIT
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Identifying common baseline clinical features of COVID-19: a scoping review
This article has 3 authors:Reviewed by ScreenIT
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Tracking the COVID-19 pandemic in Australia using genomics
This article has 21 authors:Reviewed by ScreenIT
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COVID-19 severity associates with pulmonary redistribution of CD1c+ DCs and inflammatory transitional and nonclassical monocytes
This article has 24 authors:Reviewed by ScreenIT
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Correlation between polymerase chain reaction (PCR) examination rate among the population and the containment of the COVID-19 pandemic
This article has 5 authors:Reviewed by ScreenIT
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Analysis of the time course of COVID-19 cases and deaths from countries with extensive testing allows accurate early estimates of the age specific symptomatic CFR values
This article has 5 authors:Reviewed by ScreenIT
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A Comparative Analysis of Statistical Methods to Estimate the Reproduction Number in Emerging Epidemics, With Implications for the Current Coronavirus Disease 2019 (COVID-19) Pandemic
This article has 5 authors:Reviewed by ScreenIT