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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Evidence of early community transmission of Omicron (B1.1.529) in Delhi- A city with very high seropositivity and past-exposure
This article has 11 authors:Reviewed by ScreenIT
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Development and validation of the MMCD score to predict kidney replacement therapy in COVID-19 patients
This article has 68 authors:Reviewed by ScreenIT
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Rapid and accurate identification of SARS-CoV-2 Omicron variants using droplet digital PCR (RT-ddPCR)
This article has 12 authors:Reviewed by ScreenIT
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Assessing and improving the validity of COVID-19 autopsy studies - A multicentre approach to establish essential standards for immunohistochemical and ultrastructural analyses
This article has 37 authors:Reviewed by ScreenIT
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Effect of cannabidiol on apoptosis and cellular interferon and interferon-stimulated gene responses to the SARS-CoV-2 genes ORF8, ORF10 and M protein
This article has 5 authors:Reviewed by ScreenIT
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Summaries, Analysis and Simulations of COVID-19 Epidemics in Shanghai
This article has 1 author:Reviewed by ScreenIT
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Screening for SARS-CoV-2 persistence in Long COVID patients using sniffer dogs and scents from axillary sweats samples
This article has 9 authors:Reviewed by ScreenIT
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Investigation of the Effects of N-Linked Glycans on the Stability of the Spike Protein in SARS-CoV-2 by Molecular Dynamics Simulations
This article has 1 author:Reviewed by ScreenIT
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Shift of lung macrophage composition is associated with COVID-19 disease severity and recovery
This article has 36 authors:Reviewed by ScreenIT
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Immunologic response, Efficacy, and Safety of Vaccines against COVID-19 Infection in Healthy and immunosuppressed Children and Adolescents Aged 2 – 21 years old: A Systematic Review and Meta-analysis
This article has 7 authors:Reviewed by ScreenIT