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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A SARS-CoV-2 Label-Free Surrogate Virus Neutralization Test and a Longitudinal Study of Antibody Characteristics in COVID-19 Patients
This article has 5 authors:Reviewed by ScreenIT
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Epidemiological Characteristics of Deaths from COVID-19 in Peru during the Initial Pandemic Response
This article has 12 authors:Reviewed by ScreenIT
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COVID-19 hospitalization rates rise exponentially with age, inversely proportional to thymic T-cell production
This article has 3 authors:Reviewed by ScreenIT
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Low-dose radiation therapy for COVID-19 pneumonia: a pilot study
This article has 15 authors:Reviewed by ScreenIT
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HDL-scavenger receptor B type 1 facilitates SARS-CoV-2 entry
This article has 34 authors:Reviewed by ScreenIT
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“Trained immunity” from Mycobacterium spp. exposure or BCG vaccination and COVID-19 outcomes
This article has 3 authors:Reviewed by ScreenIT
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Impact of COVID-19 upon changes in emergency room visits with chest pain of possible cardiac origin
This article has 6 authors:Reviewed by ScreenIT
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Increased Self-Reported Discrimination and Concern for Physical Assault Due to the COVID-19 Pandemic in Chinese, Vietnamese, Korean, Japanese, and Filipino Americans
This article has 9 authors:Reviewed by ScreenIT
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Laboratory based surveillance of SARS-CoV-2 in Pakistan
This article has 10 authors:Reviewed by ScreenIT
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Method for Active Pandemic Curve Management (MAPCM)
This article has 1 author:Reviewed by ScreenIT