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 role of airborne transmission in a large single source outbreak of SARS-CoV-2 in a Belgian nursing home in 2020
This article has 9 authors:Reviewed by ScreenIT
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Population Immunity and Covid-19 Severity with Omicron Variant in South Africa
This article has 11 authors:Reviewed by ScreenIT
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Mutational analysis of SARS-CoV-2. ORF8 and the evolution of the Delta and Omicron variants
This article has 2 authors:Reviewed by ScreenIT
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KNOWLEDGE, ATTITUDES AND PRACTICE AMONG HEALTHCARE WORKERS TOWARDS COVID-19 PREVENTIVE MEASURES AT WOMEN AND NEW-BORN HOSPITAL, UNIVERSITY TEACHING HOSPITAL, LUSAKA, ZAMBIA
This article has 4 authors:Reviewed by ScreenIT
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Resistance Mutations in SARS-CoV-2 Delta Variant after Sotrovimab Use
This article has 26 authors:Reviewed by ScreenIT
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The roles of APOBEC-mediated RNA editing in SARS-CoV-2 mutations, replication and fitness
This article has 7 authors:Reviewed by ScreenIT
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SARS-CoV-2 Omicron Variant: ACE2 Binding, Cryo-EM Structure of Spike Protein-ACE2 Complex and Antibody Evasion
This article has 9 authors:Reviewed by ScreenIT
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Pentosan polysulfate inhibits attachment and infection by SARS-CoV-2 in vitro : insights into structural requirements for binding
This article has 16 authors:Reviewed by ScreenIT
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Arsenal of Nanobodies for Broad-Spectrum Countermeasures against Current and Future SARS-CoV-2 Variants of Concerns
This article has 21 authors:Reviewed by ScreenIT