| Title |
Predicting Microstructure-Sensitive Fatigue-Crack Path in 3D Using a Machine Learning Framework
|
|---|---|
| Published in |
JOM, July 2019
|
| DOI | 10.1007/s11837-019-03572-y |
| Authors |
Kyle Pierson, Aowabin Rahman, Ashley D. Spear |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 50% |
| Switzerland | 1 | 17% |
| Venezuela, Bolivarian Republic of | 1 | 17% |
| Unknown | 1 | 17% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 83% |
| Science communicators (journalists, bloggers, editors) | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 93 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 93 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 16 | 17% |
| Student > Master | 12 | 13% |
| Student > Doctoral Student | 7 | 8% |
| Other | 7 | 8% |
| Researcher | 4 | 4% |
| Other | 9 | 10% |
| Unknown | 38 | 41% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 34 | 37% |
| Materials Science | 10 | 11% |
| Computer Science | 4 | 4% |
| Physics and Astronomy | 2 | 2% |
| Neuroscience | 1 | 1% |
| Other | 2 | 2% |
| Unknown | 40 | 43% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 18 August 2021.
All research outputs
#4,727,901
of 23,911,072 outputs
Outputs from JOM
#122
of 1,537 outputs
Outputs of similar age
#90,433
of 351,537 outputs
Outputs of similar age from JOM
#2
of 17 outputs
Altmetric has tracked 23,911,072 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,537 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one has done particularly well, scoring higher than 92% 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 351,537 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 74% of its contemporaries.
We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.