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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Correlates of the country differences in the infection and mortality rates during the first wave of the COVID-19 pandemic: evidence from Bayesian model averaging
This article has 5 authors:Reviewed by ScreenIT
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High-resolution profiling of pathways of escape for SARS-CoV-2 spike-binding antibodies
This article has 11 authors:Reviewed by ScreenIT
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A mathematical model to estimate percentage secondary infections from margin of error of diagnostic sensitivity: Useful tool for regulatory agencies to assess the risk of propagation due to false negative outcome of diagnostics
This article has 6 authors:Reviewed by ScreenIT
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Covid-19 respiratory protection: the filtration efficiency assessment of decontaminated FFP2 masks responding to associated shortages
This article has 8 authors:Reviewed by ScreenIT
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COVID-19 in 823 Transplant patients: A Systematic Scoping Review
This article has 7 authors:Reviewed by ScreenIT
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Reconciling epidemiological models with misclassified case-counts for SARS-CoV-2 with seroprevalence surveys: A case study in Delhi, India
This article has 5 authors:Reviewed by ScreenIT
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Age-Specific SARS-CoV-2 Infection Fatality and Case Identification Fraction in Ontario, Canada
This article has 4 authors:Reviewed by ScreenIT
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Human Surfactant Protein D Binds Spike Protein and Acts as an Entry Inhibitor of SARS-CoV-2 Pseudotyped Viral Particles
This article has 9 authors:Reviewed by ScreenIT
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Prevalence and Outcome of COVID-19 Infection in Cancer Patients: A National Veterans Affairs Study
This article has 9 authors:Reviewed by ScreenIT
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National outcomes and characteristics of patients admitted to Swedish intensive care units for COVID-19
This article has 8 authors:Reviewed by ScreenIT