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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Characterizing two outbreak waves of COVID-19 in Spain using phenomenological epidemic modelling
This article has 3 authors:Reviewed by ScreenIT
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Association Between Receipt of Unemployment Insurance and Food Insecurity Among People Who Lost Employment During the COVID-19 Pandemic in the United States
This article has 3 authors:Reviewed by ScreenIT
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The combined treatment of Molnupiravir and Favipiravir results in a marked potentiation of antiviral efficacy in a SARS-CoV-2 hamster infection model
This article has 19 authors:Reviewed by ScreenIT
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Positive association of angiotensin II receptor blockers, not angiotensin-converting enzyme inhibitors, with an increased vulnerability to SARS-CoV-2 infection in patients hospitalized for suspected COVID-19 pneumonia
This article has 16 authors:Reviewed by ScreenIT
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Predictors of Physical and Mental Health in Healthcare Teams Working with COVID-19 patients: a scoping review protocol
This article has 3 authors:Reviewed by ScreenIT
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COVID-19 Active Surveillance Simulation Case Study - Health and Economic Impacts of Active Surveillance in a School Environment
This article has 3 authors:Reviewed by ScreenIT
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An insight into SARS-CoV-2 membrane protein interaction with spike, envelope, and nucleocapsid proteins
This article has 4 authors:Reviewed by ScreenIT
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Seroprevalence of SARS-CoV-2 in Guilan Province, Iran, April 2020
This article has 9 authors:Reviewed by ScreenIT
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Single-cell Transcriptome of Bronchoalveolar Lavage Fluid Reveals Dynamic Change of Macrophages During SARS-CoV-2 Infection in Ferrets
This article has 11 authors:Reviewed by ScreenIT
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Deciphering the state of immune silence in fatal COVID-19 patients
This article has 24 authors:Reviewed by ScreenIT