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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Predictions for Europe for the Covid-19 pandemic from a SIR model
This article has 2 authors:Reviewed by ScreenIT
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The interactive effects of ambient air pollutants-meteorological factors on confirmed cases of COVID-19 in 120 Chinese cities
This article has 4 authors:Reviewed by ScreenIT
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Continuous electroencephalography characteristics and acute symptomatic seizures in COVID-19 patients
This article has 7 authors:Reviewed by ScreenIT
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Assessment of inactivation procedures for SARS-CoV-2
This article has 8 authors:Reviewed by ScreenIT
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Unspecific post-mortem findings despite multiorgan viral spread in COVID-19 patients
This article has 18 authors:Reviewed by ScreenIT
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Automated and partly automated contact tracing: a systematic review to inform the control of COVID-19
This article has 4 authors:Reviewed by ScreenIT
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Factors associated with country-variation in COVID-19 morbidity and mortality worldwide: an observational geographic study COVID-19 morbidity and mortality country-variation
This article has 3 authors:Reviewed by ScreenIT
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High Resolution CHEST CT(HRCT) Evaluation in Patients Hospitalized with COVID-19 Infection
This article has 14 authors:Reviewed by ScreenIT
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Mental Health Outcomes and Associations During the COVID-19 Pandemic: A Cross-Sectional Population-Based Study in the United States
This article has 2 authors:Reviewed by ScreenIT
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Serological identification of SARS-CoV-2 infections among children visiting a hospital during the initial Seattle outbreak
This article has 20 authors:Reviewed by ScreenIT