ScreenIT
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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Modelling the test, trace and quarantine strategy to control the COVID-19 epidemic in the state of São Paulo, Brazil
This article has 7 authors:Reviewed by ScreenIT
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Time use and social mixing during and around festive periods: Potential changes in the age distribution of COVID-19 cases from increased intergenerational interactions
This article has 5 authors:Reviewed by ScreenIT
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Persistence of SARS-CoV-2 specific B- and T-cell responses in convalescent COVID-19 patients 6-8 months after the infection
This article has 30 authors:Reviewed by ScreenIT
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Persistence of immunity to SARS-CoV-2 over time in the ski resort Ischgl
This article has 20 authors:Reviewed by ScreenIT
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Mental disorder prevalence among populations impacted by coronavirus pandemics: A multilevel meta-analytic study of COVID-19, MERS & SARS
This article has 6 authors:Reviewed by ScreenIT
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Previous psychopathology predicted severe COVID-19 concern, anxiety, and PTSD symptoms in pregnant women during “lockdown” in Italy
This article has 5 authors:Reviewed by ScreenIT
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First detection of SARS-CoV-2 genetic material in the vicinity of COVID-19 isolation Centre in Bangladesh: Variation along the sewer network
This article has 15 authors:Reviewed by ScreenIT
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Analysing different exposures identifies that wearing masks and establishing COVID-19 areas reduce secondary-attack risk in aged-care facilities
This article has 9 authors:Reviewed by ScreenIT
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“SARS-Cov-2 testing in the United Arab Emirates: Population Attitudes and Beliefs”
This article has 18 authors:Reviewed by ScreenIT
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Comparison of COVID-19 infections among healthcare workers and non-healthcare workers
This article has 7 authors:Reviewed by ScreenIT