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 cross-sectional cohort study of prevalence of antibodies to COVID-19 in Port-au-Prince, Haiti
This article has 4 authors:Reviewed by ScreenIT
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Humoral and cellular responses to mRNA vaccines against SARS-CoV-2 in patients with a history of CD20 B-cell-depleting therapy (RituxiVac): an investigator-initiated, single-centre, open-label study
This article has 20 authors:Reviewed by ScreenIT
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Anti-SARS-CoV-2 Antibody Screening in Healthcare Workers and Its Correlation with Clinical Presentation in Tertiary Care Hospital, Kathmandu, Nepal, from November 2020 to January 2021
This article has 8 authors:Reviewed by ScreenIT
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Individual-Level Heterogeneity in Mask Wearing during the COVID-19 Pandemic in Malaysia
This article has 5 authors:Reviewed by ScreenIT
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Randomized, Double Blind, Placebo Controlled, Clinical Trial to Study Ashwagandha Administration in Participants Vaccinated Against COVID-19 on Safety, Immunogenicity, and Protection With COVID-19 Vaccine–A Study Protocol
This article has 11 authors:Reviewed by ScreenIT
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Investigating the conformational dynamics of SARS-CoV-2 NSP6 protein with emphasis on non-transmembrane 91–112 & 231–290 regions
This article has 4 authors:Reviewed by ScreenIT
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Heterologous prime–boost vaccination with ChAdOx1 nCoV-19 and BNT162b2
This article has 28 authors:Reviewed by ScreenIT
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Epidemiological dynamics of SARS-CoV-2 VOC Gamma in Rio de Janeiro, Brazil
This article has 20 authors:Reviewed by ScreenIT
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Mathematical modelling of SARS-CoV-2 variant outbreaks reveals their probability of extinction
This article has 5 authors:Reviewed by ScreenIT
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Transcriptomics-inferred dynamics of SARS-CoV-2 interactions with host epithelial cells
This article has 10 authors:Reviewed by ScreenIT