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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A single intranasal or intramuscular immunization with chimpanzee adenovirus-vectored SARS-CoV-2 vaccine protects against pneumonia in hamsters
This article has 16 authors:Reviewed by ScreenIT
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Structural and Functional Characterization of SARS-CoV-2 RBD Domains Produced in Mammalian Cells
This article has 9 authors:Reviewed by ScreenIT
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Economic crisis and mental health during the COVID-19 pandemic in Japan
This article has 3 authors:Reviewed by ScreenIT
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Cross-reactive CD4 + T cells enhance SARS-CoV-2 immune responses upon infection and vaccination
This article has 37 authors:Reviewed by ScreenIT
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The indirect health impacts of COVID19 restrictions: a strong debate informed by weak evidence
This article has 5 authors:Reviewed by ScreenIT
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Associations of the BNT162b2 COVID-19 vaccine effectiveness with patient age and comorbidities
This article has 10 authors:Reviewed by ScreenIT
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Background incidence rates of hospitalisations and emergency department visits for thromboembolic and coagulation disorders in Ontario, Canada for COVID-19 vaccine safety assessment: a population-based retrospective observational study
This article has 10 authors:Reviewed by ScreenIT
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Estimating local outbreak risks and the effects of non-pharmaceutical interventions in age-structured populations: SARS-CoV-2 as a case study
This article has 3 authors:Reviewed by ScreenIT
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Physician perceptions of surveillance: Wearables, Apps, and Chatbots for COVID-19
This article has 4 authors:Reviewed by ScreenIT
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Professionals’ views on the mental health problems and vulnerability of children and young people during the early phase of the COVID-19 pandemic
This article has 12 authors:Reviewed by ScreenIT