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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Host-directed therapies against early-lineage SARS-CoV-2 retain efficacy against B.1.1.7 variant
This article has 23 authors:Reviewed by ScreenIT
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Prediction and control of COVID-19 spreading based on a hybrid intelligent model
This article has 2 authors:Reviewed by ScreenIT
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Local protection bubbles: an interpretation of the decrease in the velocity of coronavirus’s spread in the city of São Paulo
This article has 5 authors:Reviewed by ScreenIT
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Socioeconomic Disparities in Social Distancing During the COVID-19 Pandemic in the United States: Observational Study
This article has 4 authors:Reviewed by ScreenIT
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Effect of public health interventions during the first epidemic wave of COVID-19 in Cyprus: a modelling study
This article has 7 authors:Reviewed by ScreenIT
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SARS-CoV-2 Positivity in Asymptomatic-Screened Dental Patients
This article has 15 authors:Reviewed by ScreenIT
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Diagnosis of SARS-Cov-2 Infection by RT-PCR Using Specimens Other Than Naso- and Oropharyngeal Swabs: A Systematic Review and Meta-Analysis
This article has 7 authors:Reviewed by ScreenIT
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Fast Phylogeny of SARS-CoV-2 by Compression
This article has 2 authors:Reviewed by ScreenIT
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Are Epidemiological Estimates Able to Describe the Ability of Health Systems to Cope with COVID-19 Epidemic?
This article has 14 authors:Reviewed by ScreenIT
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Modeling the frequency and number of persons to test to detect and control COVID-19 outbreaks in congregate settings
This article has 6 authors:Reviewed by ScreenIT