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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Case-Control Study of Use of Personal Protective Measures and Risk for SARS-CoV 2 Infection, Thailand
This article has 21 authors:Reviewed by ScreenIT
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A scenario modeling pipeline for COVID-19 emergency planning
This article has 13 authors:Reviewed by ScreenIT
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Plasma levels of soluble ACE2are associated with sex, Metabolic Syndrome, and its biomarkers in a large cohort, pointing to a possible mechanism for increased severity in COVID-19
This article has 6 authors:Reviewed by ScreenIT
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Rotational thromboelastometry results are associated with care level in COVID-19
This article has 7 authors:Reviewed by ScreenIT
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Asymptomatic carriage rates and case fatality of SARS-CoV-2 infection in residents and staff in Irish nursing homes
This article has 8 authors:Reviewed by ScreenIT
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On the increasing incidence of SARS-CoV- 2 in older adolescents and younger adults during the epidemic in Mexico
This article has 4 authors:Reviewed by ScreenIT
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Effect of social distancing on COVID-19 incidence and mortality in the US
This article has 6 authors:Reviewed by ScreenIT
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Spatiotemporal modeling of first and second wave outbreak dynamics of COVID-19 in Germany
This article has 9 authors:Reviewed by ScreenIT
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Effects of physical activity and exercise on well-being in the context of the Covid-19 pandemic
This article has 5 authors:Reviewed by ScreenIT
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Self-reported Changes in Energy Balance Behaviors during COVID-19-related Home Confinement: A Cross-sectional Study
This article has 3 authors:Reviewed by ScreenIT