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Classification of Patients With Sepsis According to Immune Cell Characteristics: A Bioinformatic Analysis of Two Cohort Studies

Overview of attention for article published in Frontiers in Medicine, December 2020
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About this Attention Score

  • Average Attention Score compared to outputs of the same age and source

Mentioned by

peer_reviews
1 peer review site

Citations

dimensions_citation
7 Dimensions

Readers on

mendeley
20 Mendeley
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Title
Classification of Patients With Sepsis According to Immune Cell Characteristics: A Bioinformatic Analysis of Two Cohort Studies
Published in
Frontiers in Medicine, December 2020
DOI 10.3389/fmed.2020.598652
Pubmed ID
Authors

Shi Zhang, Zongsheng Wu, Wei Chang, Feng Liu, Jianfeng Xie, Yi Yang, Haibo Qiu

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 20 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 3 15%
Researcher 2 10%
Student > Master 1 5%
Student > Ph. D. Student 1 5%
Professor > Associate Professor 1 5%
Other 1 5%
Unknown 11 55%
Readers by discipline Count As %
Medicine and Dentistry 5 25%
Agricultural and Biological Sciences 1 5%
Biochemistry, Genetics and Molecular Biology 1 5%
Sports and Recreations 1 5%
Computer Science 1 5%
Other 0 0%
Unknown 11 55%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 January 2021.
All research outputs
#15,664,272
of 23,274,744 outputs
Outputs from Frontiers in Medicine
#3,168
of 5,950 outputs
Outputs of similar age
#306,622
of 509,391 outputs
Outputs of similar age from Frontiers in Medicine
#149
of 259 outputs
Altmetric has tracked 23,274,744 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,950 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.5. This one is in the 36th percentile – i.e., 36% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 509,391 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 259 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.