| Title |
Software mutational robustness
|
|---|---|
| Published in |
Genetic Programming and Evolvable Machines, July 2013
|
| DOI | 10.1007/s10710-013-9195-8 |
| Authors |
Eric Schulte, Zachary P. Fry, Ethan Fast, Westley Weimer, Stephanie Forrest |
X Demographics
The data shown below were collected from the profiles of 3 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 | 1 | 33% |
| Bosnia and Herzegovina | 1 | 33% |
| Turkey | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 67% |
| Members of the public | 1 | 33% |
Mendeley readers
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.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| China | 2 | 3% |
| United Kingdom | 1 | 1% |
| Bangladesh | 1 | 1% |
| Korea, Republic of | 1 | 1% |
| Japan | 1 | 1% |
| Unknown | 66 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 22 | 31% |
| Professor | 10 | 14% |
| Student > Master | 9 | 13% |
| Researcher | 8 | 11% |
| Student > Bachelor | 6 | 8% |
| Other | 12 | 17% |
| Unknown | 5 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 54 | 75% |
| Engineering | 4 | 6% |
| Agricultural and Biological Sciences | 2 | 3% |
| Biochemistry, Genetics and Molecular Biology | 2 | 3% |
| Business, Management and Accounting | 2 | 3% |
| Other | 1 | 1% |
| Unknown | 7 | 10% |
Attention Score in Context
This research output has an Altmetric Attention Score of 13. 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 July 2020.
All research outputs
#2,451,418
of 22,727,570 outputs
Outputs from Genetic Programming and Evolvable Machines
#3
of 121 outputs
Outputs of similar age
#22,211
of 198,144 outputs
Outputs of similar age from Genetic Programming and Evolvable Machines
#1
of 2 outputs
Altmetric has tracked 22,727,570 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 121 research outputs from this source. They receive a mean Attention Score of 3.5. This one has done particularly well, scoring higher than 97% 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 198,144 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 88% 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. This one has scored higher than all of them