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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Multiple sclerosis disease-modifying therapies and COVID-19 vaccines: a practical review and meta-analysis
This article has 9 authors:Reviewed by ScreenIT
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Correlation Between Postvaccination Anti-Spike Antibody Titers and Protection Against Breakthrough Severe Acute Respiratory Syndrome Coronavirus 2 Infection: A Population-Based Longitudinal Study
This article has 17 authors:Reviewed by ScreenIT
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Effectiveness of rapid SARS-CoV-2 genome sequencing in supporting infection control for hospital-onset COVID-19 infection: Multicentre, prospective study
This article has 51 authors:This article has been curated by 1 group: -
Underdispersion: A Statistical Anomaly in Reported Covid Data
This article has 1 author:Reviewed by ScreenIT
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Impact of COVID-19 pandemic and anti-pandemic measures on tuberculosis, viral hepatitis, HIV/AIDS and malaria – a systematic review
This article has 6 authors:Reviewed by ScreenIT
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Binding Interactions between RBD of Spike-Protein and Human ACE2 in Omicron variant
This article has 4 authors:Reviewed by ScreenIT
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Lyophilized mRNA-lipid nanoparticle vaccines with long-term stability and high antigenicity against SARS-CoV-2
This article has 34 authors:Reviewed by ScreenIT
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Engineering defensin α‐helix to produce high‐affinity SARS‐CoV ‐2 spike protein binding ligands
This article has 6 authors:Reviewed by ScreenIT
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In Vitro Selection of Remdesivir-Resistant SARS-CoV-2 Demonstrates High Barrier to Resistance
This article has 11 authors:Reviewed by ScreenIT
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Omicron (BA.1) and sub‐variants (BA.1.1, BA.2, and BA.3) of SARS‐CoV‐2 spike infectivity and pathogenicity: A comparative sequence and structural‐based computational assessment
This article has 3 authors:Reviewed by ScreenIT