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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Genetic Profiles in Pharmacogenes Indicate Personalized Drug Therapy for COVID-19
This article has 8 authors:Reviewed by ScreenIT
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A mathematical model of COVID-19 transmission between frontliners and the general public
This article has 9 authors:Reviewed by ScreenIT
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The potential impact of COVID-19 in refugee camps in Bangladesh and beyond: A modeling study
This article has 7 authors:Reviewed by ScreenIT
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Mobility traces and spreading of COVID-19
This article has 4 authors:Reviewed by ScreenIT
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Clinical features and outcomes of 197 adult discharged patients with COVID-19 in Yichang, Hubei
This article has 4 authors:Reviewed by ScreenIT
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Evaluation of the auxiliary diagnostic value of antibody assays for the detection of novel coronavirus (SARS‐CoV‐2)
This article has 7 authors:Reviewed by ScreenIT
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STeCC: Smart Testing with Contact Counting Enhances Covid-19 Mitigation by Bluetooth App Based Contact Tracing
This article has 6 authors:Reviewed by ScreenIT
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Role of Chloroquine and Hydroxychloroquine in the Treatment of COVID-19 Infection- A Systematic Literature Review
This article has 2 authors:Reviewed by ScreenIT
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Short-term forecasts and long-term mitigation evaluations for the COVID-19 epidemic in Hubei Province, China
This article has 7 authors:Reviewed by ScreenIT
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Elementary time-delay dynamics of COVID-19 disease
This article has 1 author:Reviewed by ScreenIT