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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What Has Been the Impact of Covid-19 on Safety Culture? A Case Study from a Large Metropolitan Healthcare Trust
This article has 19 authors:Reviewed by ScreenIT
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Double COVID-19 Confirmed Case Fatality Rate in Countries with High Elderly Female Vitamin D Deficiency Prevalence
This article has 2 authors:Reviewed by ScreenIT
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Rising summer temperatures do not reduce the reproduction number of COVID-19
This article has 2 authors:Reviewed by ScreenIT
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Characteristics of academic publications, preprints, and registered clinical trials on the COVID-19 pandemic
This article has 4 authors:Reviewed by ScreenIT
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Thyroid Function Abnormalities in COVID-19 Patients
This article has 13 authors:Reviewed by ScreenIT
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Global and local mobility as a barometer for COVID-19 dynamics
This article has 3 authors:Reviewed by ScreenIT
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Community seroprevalence of COVID-19 in probable and possible cases at primary health care centres in Spain
This article has 13 authors: -
The inevitability of Covid-19 related distress among healthcare workers: Findings from a low caseload country under lockdown
This article has 7 authors:Reviewed by ScreenIT
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Clinical features of 47 patients infected with COVID-19 admitted to a Regional Reference Center
This article has 10 authors:Reviewed by ScreenIT
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Transcriptogram analysis reveals relationship between viral titer and gene sets responses during Corona-virus infection
This article has 3 authors:Reviewed by ScreenIT