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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Generation of human bronchial organoids for SARS-CoV-2 research
This article has 11 authors:Reviewed by ScreenIT
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SARS-CoV-2 genome evolution exposes early human adaptations
This article has 3 authors:Reviewed by ScreenIT
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A data first approach to modelling Covid-19
This article has 1 author:Reviewed by ScreenIT
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Knowledge, Attitude, Practice, and Fear of COVID-19: an Online-Based Cross-cultural Study
This article has 13 authors:Reviewed by ScreenIT
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Bayesian network analysis of Covid-19 data reveals higher infection prevalence rates and lower fatality rates than widely reported
This article has 4 authors:Reviewed by ScreenIT
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Excess mortality in England and Wales during the first wave of the COVID-19 pandemic
This article has 5 authors:Reviewed by ScreenIT
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Multi-site Validation of a SARS-CoV-2 IgG/IgM Rapid Antibody Detection Kit
This article has 16 authors:Reviewed by ScreenIT
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Improved Detection of Antibodies against SARS-CoV-2 by Microsphere-Based Antibody Assay
This article has 17 authors:Reviewed by ScreenIT
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Pan-Family Assays for Rapid Viral Screening: Reducing Delays in Public Health Responses During Pandemics
This article has 5 authors:Reviewed by ScreenIT
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A cross-sectional study of psychological wellbeing of Indian adults during the Covid-19 lockdown: Different strokes for different folks
This article has 2 authors:Reviewed by ScreenIT