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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Has COVID-19 Hurt Resident Education? A network-wide resident survey on education and experience during the pandemic
This article has 4 authors:Reviewed by ScreenIT
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Half of children entitled to free school meals did not have access to the scheme during COVID-19 lockdown in the UK
This article has 4 authors:Reviewed by ScreenIT
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Characteristics and outcomes of hospitalized adult COVID-19 patients in Georgia
This article has 14 authors:Reviewed by ScreenIT
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A Conceptual Discussion About the Basic Reproduction Number of Severe Acute Respiratory Syndrome Coronavirus 2 in Healthcare Settings
This article has 11 authors:Reviewed by ScreenIT
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An SEIR Model with Contact Tracing and Age-Structured Social Mixing for COVID-19 outbreak
This article has 1 author:Reviewed by ScreenIT
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A preliminary model to describe the transmission dynamics of Covid-19 between two neighboring cities or countries
This article has 1 author:Reviewed by ScreenIT
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Impact of COVID-19 Shelter-in-Place Order on Transmission of Gastrointestinal Pathogens in Northern California
This article has 5 authors:Reviewed by ScreenIT
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Development and pre-clinical characterization of two therapeutic equine formulations towards SARS-CoV-2 proteins for the potential treatment of COVID-19
This article has 30 authors:Reviewed by ScreenIT
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Accessibility and allocation of public parks and gardens in England and Wales: A COVID-19 social distancing perspective
This article has 5 authors:Reviewed by ScreenIT
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Using body temperature and variables commonly available in the EHR to predict acute infection: a proof-of-concept study showing improved pretest probability estimates for acute COVID-19 infection among discharged emergency department patients
This article has 7 authors:Reviewed by ScreenIT