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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Combinations of PCR and Isothermal Amplification Techniques Are Suitable for Fast and Sensitive Detection of SARS-CoV-2 Viral RNA
This article has 5 authors:Reviewed by ScreenIT
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Risk profiles for negative and positive COVID-19 hospitalized patients
This article has 2 authors:Reviewed by ScreenIT
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Influence of COVID-19 confinement measures on appendectomies in Germany—a claims data analysis of 9797 patients
This article has 5 authors:Reviewed by ScreenIT
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Workplace exposures associated with COVID-19: evidence from a case-control study with multiple sampling periods in England, August–October 2020
This article has 8 authors:Reviewed by ScreenIT
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No Detectable Surge in SARS-CoV-2 Transmission Attributable to the April 7, 2020 Wisconsin Election
This article has 4 authors:Reviewed by ScreenIT
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Analysis of the intensity of the COVID-19 epidemic in Berlin towards an universal prognostic relationship
This article has 3 authors:Reviewed by ScreenIT
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Seroprevalence of hospital staff in a province with zero COVID-19 cases
This article has 7 authors:Reviewed by ScreenIT
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Forecasting COVID-19 pandemic: A data-driven analysis
This article has 1 author:Reviewed by ScreenIT
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Timing of elective tracheotomy and duration of mechanical ventilation among patients admitted to intensive care with severe COVID ‐19: A multicenter prospective cohort study
This article has 24 authors:Reviewed by ScreenIT
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Basrah experience among 6404 patients with COVID-19
This article has 7 authors:Reviewed by ScreenIT