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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Immune Responses to a Single Dose of the AZD1222/Covishield Vaccine at 16 Weeks in Individuals in Sri Lanka
This article has 30 authors:Reviewed by ScreenIT
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Influence of social determinants of health and county vaccination rates on machine learning models to predict COVID-19 case growth in Tennessee
This article has 5 authors: -
Right Ventricular Dysfunction in Ventilated Patients with COVID-19 (COVID-RV)
This article has 10 authors:Reviewed by ScreenIT
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Wastewater-based epidemiological surveillance to monitor the prevalence of SARS-CoV-2 in developing countries with onsite sanitation facilities
This article has 20 authors:Reviewed by ScreenIT
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COVID-19 mortality in women and men in sub-Saharan Africa: a cross-sectional study
This article has 16 authors:Reviewed by ScreenIT
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Specialized interferon ligand action in COVID19
This article has 21 authors:Reviewed by ScreenIT
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3D Printed Cobalt-Chromium-Molybdenum Porous Superalloy with Superior Antiviral Activity
This article has 6 authors:Reviewed by ScreenIT
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Influence of Novel Coronavirus COVID – 19 and HIV: A Scoping Review of Hospital Course and Symptomatology
This article has 12 authors:Reviewed by ScreenIT
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Data Analysis and Forecasting of COVID-19 Pandemic in Kuwait
This article has 4 authors:Reviewed by ScreenIT
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Collaborative maternity and newborn dashboard (CoMaND) for the COVID-19 pandemic: a protocol for timely, adaptive monitoring of perinatal outcomes in Melbourne, Australia
This article has 12 authors:Reviewed by ScreenIT