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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The Impact of Isolation Measures Due to COVID-19 on Energy Intake and Physical Activity Levels in Australian University Students
This article has 5 authors:Reviewed by ScreenIT
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Virtual Health Care for Community Management of Patients With COVID-19 in Australia: Observational Cohort Study
This article has 10 authors:Reviewed by ScreenIT
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Pre-existing Cardiovascular Disease in United States Population at High Risk for Severe COVID-19 Infection
This article has 1 author:Reviewed by ScreenIT
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The impact of goggle-associated harms to health and working status of nurses during management of COVID-19
This article has 15 authors:Reviewed by ScreenIT
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On the Generation of Medical Dialogues for COVID-19
This article has 12 authors:Reviewed by ScreenIT
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SARS-CoV-2 Antibody Seroprevalence in Industry Workers in Split-Dalmatia and Šibenik-Knin County, Croatia
This article has 9 authors:Reviewed by ScreenIT
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This article has 4 authors:
Reviewed by ScreenIT
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Anxiety, depression, attitudes, and internet addiction during the initial phase of the 2019 coronavirus disease (COVID-19) epidemic: A cross-sectional study in México
This article has 8 authors:Reviewed by ScreenIT
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Depression and anxiety during the COVID‐19 pandemic in Saudi Arabia: A cross‐sectional study
This article has 5 authors:Reviewed by ScreenIT
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Psychological distress during the COVID-19 pandemic in France: a national assessment of at-risk populations
This article has 5 authors:Reviewed by ScreenIT