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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Development of a predictive prognostic rule for early assessment of COVID-19 patients in primary care settings
This article has 6 authors:Reviewed by ScreenIT
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Comparative infection modeling and control of COVID-19 transmission patterns in China, South Korea, Italy and Iran
This article has 10 authors:Reviewed by ScreenIT
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Structure of papain-like protease from SARS-CoV-2 and its complexes with non-covalent inhibitors
This article has 21 authors:Reviewed by ScreenIT
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T Cell Activation, Highly Armed Cytotoxic Cells and a Shift in Monocytes CD300 Receptors Expression Is Characteristic of Patients With Severe COVID-19
This article has 11 authors:Reviewed by ScreenIT
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Detecting and isolating false negatives of SARS-CoV-2 primers and probe sets among the Japanese Population: A laboratory testing methodology and study
This article has 10 authors:Reviewed by ScreenIT
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Identification of risk factors contributing to COVID-19 incidence rates in Bangladesh: A GIS-based spatial modeling approach
This article has 5 authors:Reviewed by ScreenIT
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Understanding SARSCOV-2 propagation, impacting factors to derive possible scenarios and simulations
This article has 10 authors:Reviewed by ScreenIT
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Synthetic Reproduction and Augmentation of COVID-19 Case Reporting Data by Agent-Based Simulation
This article has 9 authors:Reviewed by ScreenIT
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Membrane Nanoparticles Derived from ACE2-Rich Cells Block SARS-CoV-2 Infection
This article has 15 authors:Reviewed by ScreenIT
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A globally available COVID-19 – Template for clinical imaging studies
This article has 5 authors:Reviewed by ScreenIT