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 COVID-19 Suffolk Events Toolkit (C-SET): A structured approach to conducting COVID-secure events
This article has 4 authors:Reviewed by ScreenIT
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Characteristics and outcome profile of hospitalized African patients with COVID-19: The Ethiopian context
This article has 13 authors:Reviewed by ScreenIT
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Automated contact tracing: a game of big numbers in the time of COVID-19
This article has 2 authors:Reviewed by ScreenIT
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Engineering luminescent biosensors for point-of-care SARS-CoV-2 antibody detection
This article has 19 authors:Reviewed by ScreenIT
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Geographical reconstruction of the SARS‐CoV‐2 outbreak in Lombardy (Italy) during the early phase
This article has 11 authors:Reviewed by ScreenIT
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Potential inhibitors against 2019-nCoV coronavirus M protease from clinically approved medicines
This article has 2 authors:Reviewed by ScreenIT
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Social heterogeneity and the COVID-19 lockdown in a multi-group SEIR model
This article has 2 authors:Reviewed by ScreenIT
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Is population anxiety associated with COVID-19 related hospitalizations and deaths? A study protocol
This article has 2 authors:Reviewed by ScreenIT
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Mortality, critical illness, and mechanical ventilation among hospitalized patients with COVID-19 on therapeutic anticoagulants
This article has 6 authors:Reviewed by ScreenIT
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Awareness, perception and the practice of COVID-19 prevention among residents of a state in the South-South region of Nigeria: implications for public health control efforts
This article has 15 authors:Reviewed by ScreenIT