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Timeline
X Demographics
Mendeley readers
Attention Score in Context
Title |
Application of Machine Learning in Microbiology
|
---|---|
Published in |
Frontiers in Microbiology, April 2019
|
DOI | 10.3389/fmicb.2019.00827 |
Pubmed ID | |
Authors |
Kaiyang Qu, Fei Guo, Xiangrong Liu, Yuan Lin, Quan Zou |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Venezuela, Bolivarian Republic of | 1 | 20% |
Spain | 1 | 20% |
United States | 1 | 20% |
Unknown | 2 | 40% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 3 | 60% |
Scientists | 2 | 40% |
Mendeley readers
The data shown below were compiled from readership statistics for 454 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 454 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 70 | 15% |
Student > Ph. D. Student | 69 | 15% |
Student > Master | 51 | 11% |
Student > Bachelor | 38 | 8% |
Lecturer | 18 | 4% |
Other | 62 | 14% |
Unknown | 146 | 32% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 71 | 16% |
Biochemistry, Genetics and Molecular Biology | 59 | 13% |
Engineering | 32 | 7% |
Computer Science | 30 | 7% |
Environmental Science | 25 | 6% |
Other | 70 | 15% |
Unknown | 167 | 37% |
Attention Score in Context
This research output has an Altmetric Attention Score of 18. 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 21 May 2024.
All research outputs
#2,161,641
of 26,090,071 outputs
Outputs from Frontiers in Microbiology
#1,505
of 30,097 outputs
Outputs of similar age
#46,019
of 367,104 outputs
Outputs of similar age from Frontiers in Microbiology
#59
of 646 outputs
Altmetric has tracked 26,090,071 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 30,097 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one has done particularly well, scoring higher than 94% of its peers.
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 367,104 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 646 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.