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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Estimating deaths averted and cost per life saved by scaling up mRNA COVID-19 vaccination in low-income and lower-middle-income countries in the COVID-19 Omicron variant era: a modelling study
This article has 8 authors:Reviewed by ScreenIT
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Impact of vaccination on the symptoms of hospitalised patients with SARS-CoV-2 Delta variant (B.1.617.1) infection
This article has 15 authors:Reviewed by ScreenIT
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First cases of infection with the 21L/BA.2 Omicron variant in Marseille, France
This article has 13 authors:Reviewed by ScreenIT
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Innovative Randomized Phase I Study and Dosing Regimen Selection to Accelerate and Inform Pivotal COVID‐19 Trial of Nirmatrelvir
This article has 16 authors:Reviewed by ScreenIT
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Plasticity in structure and assembly of SARS-CoV-2 nucleocapsid protein
This article has 9 authors:Reviewed by ScreenIT
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Antibody evasion properties of SARS-CoV-2 Omicron sublineages
This article has 19 authors:Reviewed by ScreenIT
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Neutralization Of SARS-CoV-2 Variants By A Human Polyclonal Antibody Therapeutic (COVID-HIG, NP-028) With High Neutralizing Titers To SARS-CoV-2
This article has 1 author:Reviewed by ScreenIT
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This article has 5 authors:
Reviewed by ScreenIT
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Olverembatinib inhibits SARS-CoV-2-Omicron variant-mediated cytokine release
This article has 3 authors:Reviewed by ScreenIT
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Trajectories of Neurologic Recovery 12 Months After Hospitalization for COVID-19
This article has 40 authors:Reviewed by ScreenIT