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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COVID19 is a seasonal climate-driven disease across both hemispheres
This article has 5 authors:Reviewed by ScreenIT
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Transcriptome profiling of different types of human respiratory tract cells infected by SARS-CoV-2 highlight an unique role for inflammatory and interferon response
This article has 11 authors:Reviewed by ScreenIT
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COVID-19 Outbreak in Algeria: A Model to Predict Cumulative Cases
This article has 1 author:Reviewed by ScreenIT
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Large scale genomic and evolutionary study reveals SARS-CoV-2 virus isolates from Bangladesh strongly correlate with European origin and not with China
This article has 19 authors:Reviewed by ScreenIT
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Quantifying hospital flows and occupancy due to COVID-19 outbreak in France. Was French lockdown effective?
This article has 1 author:Reviewed by ScreenIT
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COVID-19 and Mental Health: A Study of its Impact on Students in Maharashtra, India
This article has 3 authors:Reviewed by ScreenIT
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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) membrane (M) protein inhibits type I and III interferon production by targeting RIG-I/MDA-5 signaling
This article has 10 authors:Reviewed by ScreenIT
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Impact of COVID-19 mitigation measures on the incidence of preterm birth: a national quasi-experimental study
This article has 6 authors:Reviewed by ScreenIT
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Can herd immunity be achieved without breaking ICUs?
This article has 3 authors:Reviewed by ScreenIT
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Transmission dynamics of COVID-19 in household and community settings in the United Kingdom, January to March 2020
This article has 25 authors:Reviewed by ScreenIT