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X Demographics
Mendeley readers
Attention Score in Context
Title |
Machine Learning Applied to Identify Corrosive Environmental Conditions
|
---|---|
Published in |
Frontiers in Materials, April 2022
|
DOI | 10.3389/fmats.2022.830260 |
Authors |
HsinYen Lee, Simon Gray, Yifan Zhao, Gustavo M. Castelluccio |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 25% |
Unknown | 3 | 75% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 4 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 5 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 2 | 40% |
Researcher | 1 | 20% |
Lecturer | 1 | 20% |
Student > Doctoral Student | 1 | 20% |
Readers by discipline | Count | As % |
---|---|---|
Unspecified | 2 | 40% |
Engineering | 1 | 20% |
Unknown | 2 | 40% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 04 April 2022.
All research outputs
#14,968,328
of 23,885,338 outputs
Outputs from Frontiers in Materials
#227
of 2,733 outputs
Outputs of similar age
#218,332
of 430,328 outputs
Outputs of similar age from Frontiers in Materials
#10
of 263 outputs
Altmetric has tracked 23,885,338 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,733 research outputs from this source. They receive a mean Attention Score of 1.5. This one has done particularly well, scoring higher than 91% 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 430,328 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 263 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 96% of its contemporaries.