| Title |
Using random forests to diagnose aviation turbulence
|
|---|---|
| Published in |
Machine Learning, April 2013
|
| DOI | 10.1007/s10994-013-5346-7 |
| Pubmed ID | |
| Authors |
John K. Williams |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 25% |
| Canada | 1 | 25% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 100 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 1 | 1% |
| Unknown | 99 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 24 | 24% |
| Student > Ph. D. Student | 17 | 17% |
| Researcher | 14 | 14% |
| Student > Postgraduate | 3 | 3% |
| Student > Bachelor | 3 | 3% |
| Other | 12 | 12% |
| Unknown | 27 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 16 | 16% |
| Earth and Planetary Sciences | 15 | 15% |
| Engineering | 15 | 15% |
| Economics, Econometrics and Finance | 4 | 4% |
| Social Sciences | 4 | 4% |
| Other | 16 | 16% |
| Unknown | 30 | 30% |
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 06 April 2017.
All research outputs
#2,133,659
of 26,017,215 outputs
Outputs from Machine Learning
#50
of 1,266 outputs
Outputs of similar age
#17,301
of 211,453 outputs
Outputs of similar age from Machine Learning
#1
of 20 outputs
Altmetric has tracked 26,017,215 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 1,266 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done particularly well, scoring higher than 95% 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 211,453 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 20 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 95% of its contemporaries.