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 trans -complementation system for SARS-CoV-2
This article has 16 authors:Reviewed by ScreenIT
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Isolation of cross-reactive monoclonal antibodies against divergent human coronaviruses that delineate a conserved and vulnerable site on the spike protein
This article has 18 authors:Reviewed by ScreenIT
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COVID-19 Outbreaks in Refugee Camps
This article has 4 authors:Reviewed by ScreenIT
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Impact of climatic, demographic and disease control factors on the transmission dynamics of COVID-19 in large cities worldwide
This article has 9 authors:Reviewed by ScreenIT
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Risk Adjusted Non-Pharmaceutical Interventions for the Management of COVID-19 in South Africa
This article has 11 authors:Reviewed by ScreenIT
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Gain-of-function assay for SARS-CoV-2 M pro inhibition in living cells
This article has 6 authors:Reviewed by ScreenIT
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Tissue-specific and interferon-inducible expression of non-functional ACE2 through endogenous retrovirus co-option
This article has 7 authors:Reviewed by ScreenIT
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The impact of fear of COVID-19 on job stress, and turnover intentions of frontline nurses in the community: A cross-sectional study in the Philippines.
This article has 2 authors:Reviewed by ScreenIT
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Modelling the impact of COVID-19-related control programme interruptions on progress towards the WHO 2030 target for soil-transmitted helminths
This article has 8 authors:Reviewed by ScreenIT
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COVID-19, Diabetes, and Associated Health Outcomes in China: Results from a Nationwide Survey of 10 545 Adults
This article has 11 authors:Reviewed by ScreenIT