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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COVID-19 mRNA third dose induces a unique hybrid immunity-like antibody response
This article has 25 authors:Reviewed by ScreenIT
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Unrealistic Optimism in the Eye of the Storm: Positive Bias Towards the Consequences of COVID-19 During the Second and Third Waves of the Pandemic
This article has 7 authors:Reviewed by ScreenIT
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BA.2 and BA.5 omicron differ immunologically from both BA.1 omicron and pre-omicron variants
This article has 11 authors:Reviewed by ScreenIT
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Influencing factors of anti‐SARS‐CoV‐2‐spike‐IgG antibody titers in healthcare workers: A cross‐section study
This article has 14 authors:Reviewed by ScreenIT
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Too much to mask: determinants of sustained adherence to COVID-19 preventive measures among older Syrian refugees in Lebanon
This article has 8 authors:Reviewed by ScreenIT
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Assessing the impacts of timing on the health benefits, cost-effectiveness and relative affordability of COVID-19 vaccination programmes in 27 African Countries
This article has 14 authors:Reviewed by ScreenIT
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Mental-health before and during the COVID-19 pandemic in adults with neurodevelopmental disorders
This article has 8 authors:Reviewed by ScreenIT
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Effectiveness of influenza vaccination against SARS-CoV-2 infection among healthcare workers in Qatar
This article has 14 authors:Reviewed by ScreenIT
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Machine-Learning-Assisted Analysis of TCR Profiling Data Unveils Cross-Reactivity between SARS-CoV-2 and a Wide Spectrum of Pathogens and Other Diseases
This article has 7 authors:Reviewed by ScreenIT
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Preclinical evaluation of RQ3013, a broad-spectrum mRNA vaccine against SARS-CoV-2 variants
This article has 32 authors:Reviewed by ScreenIT