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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Addressing personal protective equipment (PPE) decontamination: Methylene blue and light inactivates severe acute respiratory coronavirus virus 2 (SARS-CoV-2) on N95 respirators and medical masks with maintenance of integrity and fit
This article has 52 authors:Reviewed by ScreenIT
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Factors associated with access to condoms and sources of condoms during the COVID-19 pandemic in South Africa
This article has 1 author:Reviewed by ScreenIT
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A systematic review of mask disinfection and reuse for SARS-CoV-2 (through July 10, 2020)
This article has 7 authors:Reviewed by ScreenIT
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UK and other SARS-CoV-2-Covariants - Simulation Modeling 70% Increase
This article has 2 authors:Reviewed by ScreenIT
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SARS-CoV-2 and the role of orofecal transmission: a systematic review
This article has 8 authors:Reviewed by ScreenIT
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COVID-19 impact on mental health
This article has 5 authors:Reviewed by ScreenIT
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Excess mortality from COVID-19: weekly excess death rates by age and sex for Sweden and its most affected region
This article has 3 authors:Reviewed by ScreenIT
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Short-term forecast in the early stage of the COVID-19 outbreak in Italy. Application of a weighted and cumulative average daily growth rate to an exponential decay model
This article has 3 authors:Reviewed by ScreenIT
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Human Embryonic Stem Cell-derived Lung Organoids: a Model for SARS-CoV-2 Infection and Drug Test
This article has 15 authors:Reviewed by ScreenIT
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The benefits of peer transparency in safe workplace operation post pandemic lockdown
This article has 5 authors:Reviewed by ScreenIT