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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Prime-boost protein subunit vaccines against SARS-CoV-2 are highly immunogenic in mice and macaques
This article has 12 authors:Reviewed by ScreenIT
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The influence of major S protein mutations of SARS-CoV-2 on the potential B cell epitopes
This article has 2 authors:Reviewed by ScreenIT
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Data-Driven Inference of COVID-19 Clinical Prognosis
This article has 4 authors:Reviewed by ScreenIT
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A compartmental epidemic model incorporating probable cases to model COVID-19 outbreak in regions with limited testing capacity
This article has 2 authors:Reviewed by ScreenIT
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Impaired performance of SARS-CoV-2 antigen-detecting rapid diagnostic tests at elevated and low temperatures
This article has 10 authors:Reviewed by ScreenIT
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Reductions in 2020 US life expectancy due to COVID-19 and the disproportionate impact on the Black and Latino populations
This article has 2 authors:Reviewed by ScreenIT
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ICU outcomes and survival in patients with severe COVID-19 in the largest health care system in central Florida
This article has 20 authors:Reviewed by ScreenIT
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Estrogen and COVID-19 symptoms: Associations in women from the COVID Symptom Study
This article has 17 authors:Reviewed by ScreenIT
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Association of Pre-COVID-19 Lymphocytopenia with Fatality
This article has 4 authors:Reviewed by ScreenIT
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Why the COVID-19 pandemic is a traumatic stressor
This article has 8 authors:Reviewed by ScreenIT