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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The utility of lung ultrasound in COVID-19: A systematic scoping review
This article has 5 authors:Reviewed by ScreenIT
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Proteomics Uncovers Immunosuppression in COVID-19 Patients with Long Disease Course
This article has 29 authors:Reviewed by ScreenIT
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Explore the Possible Impact of BCG Vaccination Policy on the Morbidity, Mortality, and Recovery Rates due to COVID-19 Infection
This article has 2 authors:Reviewed by ScreenIT
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Genomic Modeling as an Approach to Identify Surrogates for Use in Experimental Validation of SARS-CoV-2 and HuNoV Inactivation by UV-C Treatment
This article has 4 authors:Reviewed by ScreenIT
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Hypokalemia in Patients with COVID-19
This article has 34 authors:Reviewed by ScreenIT
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Compassionate use of tocilizumab in severe SARS-CoV2 pneumonia
This article has 28 authors:Reviewed by ScreenIT
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COVID-19 IN INDIA: MODELLING, FORECASTING AND STATE-WISE COMPARISON
This article has 4 authors:Reviewed by ScreenIT
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The efficacy of remdesivir in coronavirus disease 2019 (COVID-19): a systematic review
This article has 7 authors:Reviewed by ScreenIT
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A population-based study of the prevalence of COVID-19 infection in Espírito Santo, Brazil: methodology and results of the first stage
This article has 13 authors:Reviewed by ScreenIT
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Complement and tissue factor–enriched neutrophil extracellular traps are key drivers in COVID-19 immunothrombosis
This article has 17 authors:Reviewed by ScreenIT