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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SARS‐CoV‐2, an evolutionary perspective of interaction with human ACE2 reveals undiscovered amino acids necessary for complex stability
This article has 4 authors:Reviewed by ScreenIT
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AI-assisted CT imaging analysis for COVID-19 screening: Building and deploying a medical AI system
This article has 31 authors:Reviewed by ScreenIT
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Screening and managing of suspected or confirmed novel coronavirus (COVID-19) patients: experiences from a tertiary hospital outside Hubei province
This article has 4 authors:Reviewed by ScreenIT
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Forecasting Ultra-early Intensive Care Strain from COVID-19 in England, v1.1.4
This article has 7 authors:Reviewed by ScreenIT
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High incidence of asymptomatic SARS-CoV-2 infection, Chongqing, China
This article has 14 authors:Reviewed by ScreenIT
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Chinese and Italian COVID-19 outbreaks can be correctly described by a modified SIRD model
This article has 1 author:Reviewed by ScreenIT
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Climatic influences on the worldwide spread of SARS-CoV-2
This article has 4 authors:Reviewed by ScreenIT
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From the index case to global spread: the global mobility based modelling of the COVID-19 pandemic implies higher infection rate and lower detection ratio than current estimates
This article has 3 authors:Reviewed by ScreenIT
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Epidemic curve and reproduction number of COVID-19 in Iran
This article has 2 authors:Reviewed by ScreenIT
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Association between Clinical, Laboratory and CT Characteristics and RT-PCR Results in the Follow-up of COVID-19 patients
This article has 17 authors:Reviewed by ScreenIT