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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SARS-CoV-2 susceptibility of cell lines and substrates commonly used in diagnosis and isolation of influenza and other viruses
This article has 21 authors:Reviewed by ScreenIT
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Combined epidemiological and genomic analysis of nosocomial SARS-CoV-2 infection early in the pandemic and the role of unidentified cases in transmission
This article has 23 authors:Reviewed by ScreenIT
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Soap versus sanitiser for preventing the transmission of acute respiratory infections in the community: a systematic review with meta-analysis and dose–response analysis
This article has 6 authors:Reviewed by ScreenIT
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Whether the weather will help us weather the COVID-19 pandemic: Using machine learning to measure twitter users’ perceptions
This article has 6 authors:Reviewed by ScreenIT
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Susceptibility of domestic swine to experimental infection with SARS-CoV-2
This article has 7 authors:Reviewed by ScreenIT
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Single cell profiling of COVID-19 patients: an international data resource from multiple tissues
This article has 14 authors:Reviewed by ScreenIT
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Mental health of staff working in intensive care during Covid-19
This article has 6 authors:Reviewed by ScreenIT
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One Shot Model For The Prediction of COVID-19 and Lesions Segmentation In Chest CT Scans Through The Affinity Among Lesion Mask Features
This article has 1 author:Reviewed by ScreenIT
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The efficacy of IL-6 inhibitor Tocilizumab in reducing severe COVID-19 mortality: a systematic review
This article has 2 authors:Reviewed by ScreenIT
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Alcohol Consumption Is Associated with Poor Prognosis in Obese Patients with COVID-19: A Mendelian Randomization Study Using UK Biobank
This article has 8 authors:Reviewed by ScreenIT