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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Monitoring disease transmissibility of 2019 novel coronavirus disease in Zhejiang, China
This article has 12 authors:Reviewed by ScreenIT
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Significance of hydrophobic and charged sequence similarities in sodium-bile acid cotransporter and vitamin D-binding protein macrophage activating factor
This article has 3 authors:Reviewed by ScreenIT
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Rapid metagenomic characterization of a case of imported COVID-19 in Cambodia
This article has 18 authors:Reviewed by ScreenIT
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A novel bat coronavirus reveals natural insertions at the S1/S2 cleavage site of the Spike protein and a possible recombinant origin of HCoV-19
This article has 13 authors:Reviewed by ScreenIT
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Epidemiology and transmission of COVID-19 in 391 cases and 1286 of their close contacts in Shenzhen, China: a retrospective cohort study
This article has 22 authors:Reviewed by ScreenIT
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Lymphopenia predicts disease severity of COVID-19: a descriptive and predictive study
This article has 8 authors:Reviewed by ScreenIT
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Systematic review of the registered clinical trials for coronavirus disease 2019 (COVID-19)
This article has 6 authors:Reviewed by ScreenIT
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Association of Cardiovascular Manifestations with In-hospital Outcomes in Patients with COVID-19: A Hospital Staff Data
This article has 8 authors:Reviewed by ScreenIT
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Evidence for host-dependent RNA editing in the transcriptome of SARS-CoV-2
This article has 5 authors:Reviewed by ScreenIT
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Crystal structure of Nsp15 endoribonuclease NendoU from SARS-CoV-2
This article has 7 authors:Reviewed by ScreenIT