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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Rapid production of clinical‐grade SARS‐CoV‐2 specific T cells
This article has 14 authors:Reviewed by ScreenIT
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Susceptibility of tree shrew to SARS-CoV-2 infection
This article has 22 authors:Reviewed by ScreenIT
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SARS-CoV-2 selectively mimics a cleavable peptide of human ENaC in a strategic hijack of host proteolytic machinery
This article has 5 authors:Reviewed by ScreenIT
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Origin of imported SARS-CoV-2 strains in The Gambia identified from Whole Genome Sequences
This article has 18 authors:Reviewed by ScreenIT
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Insurgence and worldwide diffusion of genomic variants in SARS-CoV-2 genomes
This article has 16 authors:Reviewed by ScreenIT
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Estimating cumulative incidence of SARS-CoV-2 with imperfect serological tests: exploiting cutoff-free approaches
This article has 4 authors:Reviewed by ScreenIT
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Public Perceptions of COVID-19 in Australia: Perceived Risk, Knowledge, Health-Protective Behaviors, and Vaccine Intentions
This article has 2 authors:Reviewed by ScreenIT
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Empowering Virus Sequences Research through Conceptual Modeling
This article has 4 authors:Reviewed by ScreenIT
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Tracing Back the Temporal Change of SARS-CoV-2 with Genomic Signatures
This article has 4 authors:Reviewed by ScreenIT
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A deeper look at COVID-19 CFR: health care impact and roots of discrepancy
This article has 3 authors:Reviewed by ScreenIT