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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COVID-19 in multiple sclerosis patients and risk factors for severe infection
This article has 15 authors:Reviewed by ScreenIT
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Lopinavir-Ritonavir in the Treatment of COVID-19: A Dynamic Systematic Benefit-Risk Assessment
This article has 8 authors:Reviewed by ScreenIT
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Belief in a COVID-19 Conspiracy Theory as a Predictor of Mental Health and Well-Being of Health Care Workers in Ecuador: Cross-Sectional Survey Study
This article has 7 authors:Reviewed by ScreenIT
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Knowledge, attitude, and perceptions towards the 2019 Coronavirus Pandemic: A bi-national survey in Africa
This article has 6 authors:Reviewed by ScreenIT
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This article has 2 authors:
Reviewed by ScreenIT
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Study protocol for COvid-19 Vascular sERvice (COVER) study: The impact of the COVID-19 pandemic on the provision, practice and outcomes of vascular surgery
This article has 3 authors:Reviewed by ScreenIT
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A pilot study to investigate the fecal dissemination of SARS-CoV-2 virus genome in COVID-19 patients in Odisha, India
This article has 6 authors:Reviewed by ScreenIT
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Can medication mitigate the need for a strict lock down?: A mathematical study of control strategies for COVID-19 infection
This article has 3 authors:Reviewed by ScreenIT
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Early impact of COVID ‐19 on individuals with self‐reported eating disorders: A survey of ~1,000 individuals in the United States and the Netherlands
This article has 10 authors:Reviewed by ScreenIT
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Duration of SARS‐CoV‐2 detection in Israel Defense Forces soldiers with mild COVID‐19
This article has 3 authors:Reviewed by ScreenIT