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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Assessing the safety of home oximetry for COVID-19: a multisite retrospective observational study
This article has 8 authors:Reviewed by ScreenIT
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Random time transformation analysis of Covid19 2020
This article has 2 authors:Reviewed by ScreenIT
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Nafamostat Mesylate in lipid carrier for nasal SARS-CoV2 titer reduction in a hamster model
This article has 9 authors:Reviewed by ScreenIT
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SARS-CoV2-mediated suppression of NRF2-signaling reveals potent antiviral and anti-inflammatory activity of 4-octyl-itaconate and dimethyl fumarate
This article has 38 authors:Reviewed by ScreenIT
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Development and Validation of the Patient History COVID-19 (PH-Covid19) Scoring System: A Multivariable Prediction Model of Death in Mexican Patients with COVID-19
This article has 9 authors:Reviewed by ScreenIT
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pH Effect on the Dynamics of SARS-CoV-2 Main Protease (M pro )
This article has 2 authors:Reviewed by ScreenIT
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A demographic scaling model for estimating the total number of COVID-19 infections
This article has 3 authors:Reviewed by ScreenIT
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How many COVID-19 PCR positive individuals do we expect to see on the Diamond Princess cruise ship?
This article has 6 authors:Reviewed by ScreenIT
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Officially Confirmed COVID-19 and Unreported COVID-19–Like Illness Death Counts: An Assessment of Reporting Discrepancy in Bangladesh
This article has 4 authors:Reviewed by ScreenIT
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Automatic Detection of COVID-19 and Pneumonia from Chest X-Ray using Transfer Learning
This article has 2 authors:Reviewed by ScreenIT