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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Adapting Lot Quality Assurance Sampling to accommodate imperfect tests: application to COVID-19 serosurveillance in Haiti
This article has 5 authors:Reviewed by ScreenIT
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A SARS‐CoV‐2 Spike Binding DNA Aptamer that Inhibits Pseudovirus Infection by an RBD‐Independent Mechanism**
This article has 7 authors:Reviewed by ScreenIT
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Nowcasting COVID-19 Deaths in England by Age and Region
This article has 4 authors:Reviewed by ScreenIT
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Two-Stage Adaptive Pooling with RT-qPCR for COVID-19 Screening
This article has 2 authors:Reviewed by ScreenIT
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Risk Factors Associated With Mortality Among Residents With Coronavirus Disease 2019 (COVID-19) in Long-term Care Facilities in Ontario, Canada
This article has 5 authors:Reviewed by ScreenIT
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Neutralizing antibody-dependent and -independent immune responses against SARS-CoV-2 in cynomolgus macaques
This article has 8 authors:Reviewed by ScreenIT
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Correlating Covid-19 mortality and infection levels
This article has 2 authors:Reviewed by ScreenIT
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A simple model to assess Wuhan lock-down effect and region efforts during COVID-19 epidemic in China Mainland
This article has 5 authors:Reviewed by ScreenIT
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The decrease in hospitalizations for transient ischemic attack and ischemic stroke, especially in mild cases, during the COVID-19 epidemic in Japan
This article has 6 authors:Reviewed by ScreenIT
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Computer-aided covid-19 patient screening using chest images (X-Ray and CT scans)
This article has 1 author:Reviewed by ScreenIT