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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Holder Pasteurization Inactivates SARS-CoV-2 in Human Breast Milk
This article has 11 authors:Reviewed by ScreenIT
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Pervasive RNA Secondary Structure in the Genomes of SARS-CoV-2 and Other Coronaviruses
This article has 1 author:Reviewed by ScreenIT
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Genome-wide CRISPR screen reveals host genes that regulate SARS-CoV-2 infection
This article has 27 authors:Reviewed by ScreenIT
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A thermostable, closed SARS-CoV-2 spike protein trimer
This article has 88 authors:Reviewed by ScreenIT
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HiDeF: identifying persistent structures in multiscale ‘omics data
This article has 6 authors:Reviewed by ScreenIT
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Time-series analyses of directional sequence changes in SARS-CoV-2 genomes and an efficient search method for candidates for advantageous mutations for growth in human cells
This article has 3 authors:Reviewed by ScreenIT
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Effect of SARS-CoV-2 antibody screening on participants' attitudes and behaviour: a study of industry workers in Split, Croatia
This article has 10 authors:Reviewed by ScreenIT
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Clinical, immunological and virological characterization of COVID-19 patients that test re-positive for SARS-CoV-2 by RT-PCR
This article has 18 authors:Reviewed by ScreenIT
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National Early Warning Scores and COVID-19 deaths in care homes: a longitudinal ecological study
This article has 4 authors:Reviewed by ScreenIT
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Self-reported food choices before and during COVID-19 lockdown
This article has 5 authors:Reviewed by ScreenIT