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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A model-based approach to improve intranasal sprays for respiratory viral infections
This article has 11 authors:Reviewed by ScreenIT
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Performance of Various Lateral Flow SARS-CoV-2 Antigen Self Testing Methods in Healthcare Workers: a Multicenter Study
This article has 14 authors:Reviewed by ScreenIT
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Screening for Severe Acute Respiratory Syndrome Coronavirus 2 in Close Contacts of Individuals With Confirmed Infection: Performance and Operational Considerations
This article has 22 authors:Reviewed by ScreenIT
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Agility and Sustainability: A Qualitative Evaluation of COVID-19 Non-pharmaceutical Interventions in the UK Logistics Sector
This article has 9 authors:Reviewed by ScreenIT
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Harringtonine has the effects of double blocking SARS-CoV-2 membrane fusion
This article has 30 authors:Reviewed by ScreenIT
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SARS-CoV-2 N501Y Introductions and Transmissions in Switzerland from Beginning of October 2020 to February 2021—Implementation of Swiss-Wide Diagnostic Screening and Whole Genome Sequencing
This article has 46 authors:Reviewed by ScreenIT
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Assessing the impact of lateral flow testing strategies on within-school SARS-CoV-2 transmission and absences: A modelling study
This article has 6 authors:Reviewed by ScreenIT
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SARS‐CoV‐2 RNA stability in dry swabs for longer storage and transport at different temperatures
This article has 11 authors:Reviewed by ScreenIT
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Inclusion of cycle threshold (CT) values when reporting SARS-CoV-2 RT-PCR results improves clinical Interpretation in suspected and confirmed COVID-19
This article has 21 authors:Reviewed by ScreenIT
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SARS-CoV-2 genome surveillance in Mainz, Germany, reveals convergent origin of the N501Y spike mutation in a hospital setting
This article has 13 authors:Reviewed by ScreenIT