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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Neutralizing efficacy of vaccines against the SARS-CoV-2 Mu variant
This article has 4 authors:Reviewed by ScreenIT
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The International Sexual Health And REproductive Health during COVID-19 (I-SHARE) Study: A Multicountry Analysis of Adults from 30 Countries Prior to and During the Initial Coronavirus Disease 2019 Wave
This article has 56 authors:Reviewed by ScreenIT
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The pandemic brain: Neuroinflammation in non-infected individuals during the COVID-19 pandemic
This article has 23 authors:Reviewed by ScreenIT
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Lasting Changes to Circulating Leukocytes in People with Mild SARS-CoV-2 Infections
This article has 24 authors:Reviewed by ScreenIT
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Chronic inflammation, neutrophil activity, and autoreactivity splits long COVID
This article has 25 authors:Reviewed by ScreenIT
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Household and social characteristics associated with COVID-19 vaccine intent among Latino families in the San Francisco Bay Area
This article has 4 authors:Reviewed by ScreenIT
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Quantification and prognostic significance of interferon-γ secreting SARS-CoV-2 responsive T cells in hospitalized patients with acute COVID-19
This article has 19 authors:Reviewed by ScreenIT
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COVID-19 Vaccine Breakthrough Infections in Veterans Health Administration
This article has 3 authors:Reviewed by ScreenIT
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Contact surveys reveal heterogeneities in age-group contributions to SARS-CoV-2 dynamics in the United States
This article has 4 authors:Reviewed by ScreenIT
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Prevalence and risk factors for in-school transmission of SARS-CoV-2 in Massachusetts K-12 public schools, 2020-2021
This article has 6 authors: