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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Fear, Anxiety, Stress, and Depression of Novel Coronavirus (COVID-19) Pandemic Among Patients and Their Healthcare Workers – A Descriptive Study
This article has 8 authors:Reviewed by ScreenIT
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SARS-CoV-2 mRNA Vaccines Elicit Different Responses in Immunologically Naïve and Pre-Immune Humans
This article has 7 authors:Reviewed by ScreenIT
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Use of medicinal plants for COVID-19 prevention and respiratory symptom treatment during the pandemic in Cusco, Peru: A cross-sectional survey
This article has 10 authors:Reviewed by ScreenIT
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Computational decomposition reveals reshaping of the SARS‐CoV‐2–ACE2 interface among viral variants expressing the N501Y mutation
This article has 7 authors:Reviewed by ScreenIT
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Antibody Response to CoronaVac Vaccine in Indonesian COVID-19 Survivor
This article has 3 authors:Reviewed by ScreenIT
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Inference of the SARS-CoV-2 generation time using UK household data
This article has 9 authors:This article has been curated by 1 group: -
Assessment of Out-of-Pocket Spending for COVID-19 Hospitalizations in the US in 2020
This article has 3 authors:Reviewed by ScreenIT
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Antibody Display of cell surface receptor Tetraspanin12 and SARS-CoV-2 spike protein
This article has 2 authors:Reviewed by ScreenIT
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The real-life impact of vaccination on COVID-19 mortality in Europe and Israel
This article has 3 authors:Reviewed by ScreenIT
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Time scale performance of rapid antigen testing for SARS‐CoV‐2: Evaluation of 10 rapid antigen assays
This article has 11 authors:Reviewed by ScreenIT