The data shown below were compiled from readership statistics for 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Mendeley readers
Attention Score in Context
Title |
General Multi-Fidelity Framework for Training Artificial Neural Networks With Computational Models
|
---|---|
Published in |
Frontiers in Materials, April 2019
|
DOI | 10.3389/fmats.2019.00061 |
Authors |
Roland Can Aydin, Fabian Albert Braeu, Christian Johannes Cyron |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 72 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 14 | 19% |
Researcher | 13 | 18% |
Student > Master | 7 | 10% |
Professor | 4 | 6% |
Student > Doctoral Student | 4 | 6% |
Other | 6 | 8% |
Unknown | 24 | 33% |
Readers by discipline | Count | As % |
---|---|---|
Engineering | 23 | 32% |
Computer Science | 5 | 7% |
Materials Science | 4 | 6% |
Mathematics | 3 | 4% |
Physics and Astronomy | 3 | 4% |
Other | 5 | 7% |
Unknown | 29 | 40% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 07 August 2024.
All research outputs
#5,769,795
of 26,504,585 outputs
Outputs from Frontiers in Materials
#100
of 3,140 outputs
Outputs of similar age
#106,731
of 367,452 outputs
Outputs of similar age from Frontiers in Materials
#10
of 50 outputs
Altmetric has tracked 26,504,585 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,140 research outputs from this source. They receive a mean Attention Score of 1.6. This one has done particularly well, scoring higher than 96% 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 367,452 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 50 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.