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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Multi-parameter formulation development for an HIV-vaccine protein with direct validation of epitope binding integrity and stoichiometry
This article has 7 authors:Reviewed by ScreenIT
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SARS-CoV-2 Infection Drives a Glycan Switch of Peripheral T Cells at Diagnosis
This article has 12 authors:Reviewed by ScreenIT
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Identification of SARS‐CoV‐2 RNA in healthcare heating, ventilation, and air conditioning units
This article has 9 authors: -
Depression and Associated Factors Among Refugees Amidst Covid-19 in Nakivale Refugee Camp in Uganda
This article has 4 authors:Reviewed by ScreenIT
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In vitro activity of itraconazole against SARS‐CoV‐2
This article has 11 authors:Reviewed by ScreenIT
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Reliability of Google Trends: Analysis of the Limits and Potential of Web Infoveillance During COVID-19 Pandemic and for Future Research
This article has 1 author:Reviewed by ScreenIT
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Cross-neutralization of SARS-CoV-2 by HIV-1 specific broadly neutralizing antibodies and polyclonal plasma
This article has 12 authors:Reviewed by Review Commons, ScreenIT
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The Psychological Impact of Coronavirus on University Students and its Socio-Economic Determinants in Malaysia
This article has 5 authors:Reviewed by ScreenIT
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Digital contact-tracing during the Covid-19 pandemic: An analysis of newspaper coverage in Germany, Austria, and Switzerland
This article has 3 authors:Reviewed by ScreenIT
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Mass spectrometric based detection of protein nucleotidylation in the RNA polymerase of SARS-CoV-2
This article has 4 authors:Reviewed by ScreenIT