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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Modelling of the second (and subsequent) waves of the coronavirus epidemic. Spain and Germany as case studies
This article has 1 author:Reviewed by ScreenIT
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Assessing the potential impact of transmission during prolonged viral shedding on the effect of lockdown relaxation on COVID-19
This article has 8 authors:Reviewed by ScreenIT
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How to better communicate the exponential growth of infectious diseases
This article has 2 authors:Reviewed by ScreenIT
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Cross-reactivity of neutralizing antibody and its correlation with circulating T follicular cells in recovered COVID-19 individuals
This article has 34 authors:Reviewed by ScreenIT
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COVID-19 infections among Healthcare Workers and Transmission within Households
This article has 8 authors:Reviewed by ScreenIT
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Transformed time series analysis of first-wave COVID-19: universal similarities found in the Group of Twenty (G20) Countries
This article has 1 author:Reviewed by ScreenIT
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Assessment of SARS-CoV-2 infection by Reverse transcription-PCR and serology in the Paris area: a cross-sectional study
This article has 18 authors:Reviewed by ScreenIT
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Global research trend in the treatment of the new Coronavirus diseases (COVID-19): bibliometric analysis
This article has 2 authors:Reviewed by ScreenIT
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Simultaneous detection and mutation surveillance of SARS-CoV-2 and multiple respiratory viruses by rapid field-deployable sequencing
This article has 15 authors:Reviewed by ScreenIT
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COVID-19 challenges to dentistry in the new pandemic epicenter: Brazil
This article has 10 authors:Reviewed by ScreenIT