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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Second versus first wave of COVID-19 deaths: Shifts in age distribution and in nursing home fatalities
This article has 3 authors:Reviewed by ScreenIT
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The effect of large-scale anti-contagion policies on the COVID-19 pandemic
This article has 15 authors:Reviewed by ScreenIT
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Systematic Review and Patient‐Level Meta‐Analysis of SARS‐CoV‐2 Viral Dynamics to Model Response to Antiviral Therapies
This article has 10 authors:Reviewed by ScreenIT
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Endocrine disrupting chemicals and COVID-19 relationships: A computational systems biology approach
This article has 5 authors:Reviewed by ScreenIT
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Does BCG protect against SARS-CoV-2 infection ?: elements of proof
This article has 11 authors:Reviewed by ScreenIT
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Racial/Ethnic Disparities in COVID-19 Hospital Admissions
This article has 8 authors:Reviewed by ScreenIT
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Monitoring COVID-19 related public Interest and population Health Literacy in South Asia: An Internet Search-Interest Based Model
This article has 2 authors:Reviewed by ScreenIT
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Long-term neurological manifestations of COVID-19: prevalence and predictive factors
This article has 15 authors:Reviewed by ScreenIT
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Evaluation of the Effect of Zinc, Quercetin, Bromelain and Vitamin C on COVID-19 Patients
This article has 6 authors:Reviewed by ScreenIT
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First proof of the capability of wastewater surveillance for COVID-19 in India through detection of genetic material of SARS-CoV-2
This article has 7 authors:Reviewed by ScreenIT