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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The impact of SARS-CoV-2 vaccination on Alpha and Delta variant transmission
This article has 8 authors:Reviewed by ScreenIT
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In silico screening of TMPRSS2 SNPs that affect its binding with SARS-CoV2 spike protein and directly involved in the interaction affinity changes
This article has 12 authors:Reviewed by ScreenIT
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Persistence of Robust Humoral Immune Response in Coronavirus Disease 2019 Convalescent Individuals Over 12 Months After Infection
This article has 20 authors:Reviewed by ScreenIT
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Durability of ChAdOx1 nCoV-19 vaccination in people living with HIV
This article has 58 authors:Reviewed by ScreenIT
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Prediction of hospital-onset COVID-19 infections using dynamic networks of patient contact: an international retrospective cohort study
This article has 15 authors:Reviewed by ScreenIT
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Persistence of neuropsychiatric symptoms associated with SARS-CoV-2 positivity among a cohort of children and adolescents
This article has 3 authors:Reviewed by ScreenIT
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Predictors of Real-World Parents’ Acceptance to Vaccinate Their Children Against the COVID-19
This article has 7 authors:Reviewed by ScreenIT
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A brief analysis of the COVID-19 death data in Malaysia
This article has 9 authors:Reviewed by ScreenIT
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Prevalence of SARS-CoV-2: An age-stratified, population-based, sero-epidemiological survey in Islamabad, Pakistan
This article has 14 authors:Reviewed by ScreenIT
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Inequalities in COVID-19 inequalities research: Who had the capacity to respond?
This article has 7 authors:Reviewed by ScreenIT