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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Easing COVID-19 lockdown measures while protecting the older restricts the deaths to the level of the full lockdown
This article has 3 authors:Reviewed by ScreenIT
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Lactate Arterial-Central Venous Gradient among COVID-19 Patients in ICU: A Potential Tool in the Clinical Practice
This article has 7 authors:Reviewed by ScreenIT
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A Two-wave Epidemiological model of COVID-19 outbreaks using MS-Excel®
This article has 4 authors:Reviewed by ScreenIT
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Estimation of the Number of General Anesthesia Cases Based on a Series of Nationwide Surveys on Twitter during COVID-19 Pandemic in Japan: A Statistical Analysis
This article has 3 authors:Reviewed by ScreenIT
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Systematic benefit-risk assessment for the use of chloroquine or hydroxychloroquine as a treatment for COVID-19: Establishing a dynamic framework for rapid decision-making
This article has 7 authors:Reviewed by ScreenIT
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Total predicted MHC-I epitope load is inversely associated with population mortality from SARS-CoV-2
This article has 4 authors:Reviewed by ScreenIT
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Placental Pathology in COVID-19
This article has 6 authors:Reviewed by ScreenIT
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Outcomes Among HIV-Positive Patients Hospitalized With COVID-19
This article has 9 authors:Reviewed by ScreenIT
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ACE2 localizes to the respiratory cilia and is not increased by ACE inhibitors or ARBs
This article has 39 authors:Reviewed by ScreenIT
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Tracking COVID-19 using taste and smell loss Google searches is not a reliable strategy
This article has 5 authors:Reviewed by ScreenIT