| Title |
High-Dimensional Materials and Process Optimization Using Data-Driven Experimental Design with Well-Calibrated Uncertainty Estimates
|
|---|---|
| Published in |
Integrating Materials and Manufacturing Innovation, July 2017
|
| DOI | 10.1007/s40192-017-0098-z |
| Authors |
Julia Ling, Maxwell Hutchinson, Erin Antono, Sean Paradiso, Bryce Meredig |
X Demographics
The data shown below were collected from the profiles of 20 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 | 9 | 45% |
| India | 2 | 10% |
| Italy | 1 | 5% |
| United Kingdom | 1 | 5% |
| Unknown | 7 | 35% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 11 | 55% |
| Scientists | 9 | 45% |
Mendeley readers
The data shown below were compiled from readership statistics for 294 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | <1% |
| Unknown | 293 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 76 | 26% |
| Researcher | 62 | 21% |
| Student > Master | 21 | 7% |
| Student > Doctoral Student | 13 | 4% |
| Other | 12 | 4% |
| Other | 42 | 14% |
| Unknown | 68 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Materials Science | 61 | 21% |
| Engineering | 48 | 16% |
| Chemistry | 24 | 8% |
| Computer Science | 23 | 8% |
| Physics and Astronomy | 19 | 6% |
| Other | 30 | 10% |
| Unknown | 89 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 29. 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 09 November 2022.
All research outputs
#1,325,135
of 25,085,000 outputs
Outputs from Integrating Materials and Manufacturing Innovation
#4
of 62 outputs
Outputs of similar age
#25,983
of 318,753 outputs
Outputs of similar age from Integrating Materials and Manufacturing Innovation
#2
of 2 outputs
Altmetric has tracked 25,085,000 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 62 research outputs from this source. They receive a mean Attention Score of 4.8. 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 318,753 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 2 others from the same source and published within six weeks on either side of this one.