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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Disease severity-specific neutrophil signatures in blood transcriptomes stratify COVID-19 patients
This article has 56 authors:Reviewed by ScreenIT
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COVID-19 mortality risk assessment: An international multi-center study
This article has 19 authors:Reviewed by ScreenIT
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Correlation of ELISA based with random access serologic immunoassays for identifying adaptive immune response to SARS-CoV-2
This article has 16 authors:Reviewed by ScreenIT
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Rapid triage for COVID-19 using routine clinical data for patients attending hospital: development and prospective validation of an artificial intelligence screening test
This article has 10 authors:Reviewed by ScreenIT
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Reflection of connectivism in medical education and learning motivation during COVID-19
This article has 4 authors:Reviewed by ScreenIT
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Genes encoding ACE2, TMPRSS2 and related proteins mediating SARS-CoV-2 viral entry are upregulated with age in human cardiomyocytes
This article has 6 authors:Reviewed by ScreenIT
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A rapidly adaptable biomaterial vaccine for SARS-CoV-2
This article has 10 authors:Reviewed by ScreenIT
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Spike protein fusion loop controls SARS-CoV-2 fusogenicity and infectivity
This article has 1 author:Reviewed by ScreenIT
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Alignment of virus-host protein-protein interaction networks by integer linear programming: SARS-CoV-2
This article has 2 authors:Reviewed by ScreenIT
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A fluorescence-based high throughput-screening assay for the SARS-CoV RNA synthesis complex
This article has 7 authors:Reviewed by ScreenIT