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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mRNA-based vaccines against SARS-CoV-2 do not stimulate interferon stimulatory gene expression in individuals affected by Aicardi Goutières Syndrome
This article has 18 authors:Reviewed by ScreenIT
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The Effect of Fear of Infection and Sufficient Vaccine Reservation Information on Rapid COVID-19 Vaccination in Japan: Evidence From a Retrospective Twitter Analysis
This article has 5 authors:Reviewed by ScreenIT
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COVID-19 booster dose induces robust antibody response in pregnant, lactating, and nonpregnant women
This article has 17 authors:Reviewed by ScreenIT
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Reduced Antibody Acquisition with Increasing Age following Vaccination with BNT162b2: Results from Two Longitudinal Cohort Studies in The Netherlands
This article has 22 authors:Reviewed by ScreenIT
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Reduced Exercise Capacity, Chronotropic Incompetence, and Early Systemic Inflammation in Cardiopulmonary Phenotype Long Coronavirus Disease 2019
This article has 25 authors:Reviewed by ScreenIT
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Comprehensive analysis of pathways in Coronavirus 2019 (COVID-19) using an unsupervised machine learning method
This article has 2 authors:Reviewed by ScreenIT
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Real-world comparative effectiveness of mRNA-1273 and BNT162b2 vaccines among immunocompromised adults identified in administrative claims data in the United States
This article has 12 authors:Reviewed by ScreenIT
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SARS-CoV-2 Subunit Virus-Like Vaccine Demonstrates High Safety Profile and Protective Efficacy: Preclinical Study
This article has 14 authors:Reviewed by ScreenIT
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Using unsupervised learning algorithms to identify essential genes associated with SARS-CoV-2 as potential therapeutic targets for COVID-19
This article has 2 authors:Reviewed by ScreenIT
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Molecular analysis of a public cross-neutralizing antibody response to SARS-CoV-2
This article has 6 authors:Reviewed by ScreenIT