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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Epidemiological and Genomic Analysis of SARS-CoV-2 in 10 Patients From a Mid-Sized City Outside of Hubei, China in the Early Phase of the COVID-19 Outbreak
This article has 11 authors:Reviewed by ScreenIT
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Development and validation of an early warning score (EWAS) for predicting clinical deterioration in patients with coronavirus disease 2019
This article has 30 authors:Reviewed by ScreenIT
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Early forecasts of the evolution of the COVID-19 outbreaks and quantitative assessment of the effectiveness of countering measures
This article has 2 authors:Reviewed by ScreenIT
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The effect of travel restrictions on the geographical spread of COVID-19 between large cities in China: a modelling study
This article has 37 authors:Reviewed by ScreenIT
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Two patients with acute meningoencephalitis concomitant with SARS‐CoV‐2 infection
This article has 9 authors:Reviewed by ScreenIT
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Development and multicenter performance evaluation of fully automated SARS-CoV-2 IgM and IgG immunoassays
This article has 20 authors:Reviewed by ScreenIT
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Sequencing identifies multiple early introductions of SARS-CoV-2 to the New York City region
This article has 45 authors:Reviewed by ScreenIT
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Multi-task deep learning based CT imaging analysis for COVID-19 pneumonia: Classification and segmentation
This article has 4 authors:Reviewed by ScreenIT
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Interplay of host regulatory network on SARS-CoV-2 binding and replication machinery
This article has 6 authors:Reviewed by ScreenIT
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Integrated analyses of single-cell atlases reveal age, gender, and smoking status associations with cell type-specific expression of mediators of SARS-CoV-2 viral entry and highlights inflammatory programs in putative target cells
This article has 104 authors:Reviewed by ScreenIT