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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Comparing SARS-CoV-2 case rates between pupils, teachers and the general population: results from Germany
This article has 5 authors:Reviewed by ScreenIT
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Real-world evidence for improved outcomes with histamine antagonists and aspirin in 22,560 COVID-19 patients
This article has 6 authors:Reviewed by ScreenIT
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In Vitro Analysis of the Anti-viral Potential of nasal spray constituents against SARS-CoV-2
This article has 5 authors:Reviewed by ScreenIT
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Broad-Spectrum, Patient-Adaptable Inhaled Niclosamide-Lysozyme Particles are Efficacious Against Coronaviruses in Lethal Murine Infection Models
This article has 6 authors:Reviewed by ScreenIT
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Development of Remdesivir as a Dry Powder for Inhalation by Thin Film Freezing
This article has 5 authors:Reviewed by ScreenIT
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Predicting mortality of individual patients with COVID-19: a multicentre Dutch cohort
This article has 36 authors:Reviewed by ScreenIT
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An Automated Dashboard to Improve Laboratory COVID-19 Diagnostics Management
This article has 6 authors:Reviewed by ScreenIT
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Meta-analysis and adjusted estimation of COVID-19 case fatality risk in India and its association with the underlying comorbidities
This article has 9 authors:Reviewed by ScreenIT
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Exploring the behavioral determinants of COVID-19 vaccine acceptance among an urban population in Bangladesh: Implications for behavior change interventions
This article has 9 authors:Reviewed by ScreenIT
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COVID-19 pandemic: Analyzing of different pandemic control strategies using saturation models
This article has 2 authors:Reviewed by ScreenIT