| Title |
An Improved Parameter Estimation Method for Hodgkin-Huxley Models
|
|---|---|
| Published in |
Journal of Computational Neuroscience, March 1999
|
| DOI | 10.1023/a:1008880518515 |
| Pubmed ID | |
| Authors |
Allan R. Willms, Deborah J. Baro, Ronald M. Harris-Warrick, John Guckenheimer |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 115 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 4 | 3% |
| Spain | 3 | 3% |
| France | 3 | 3% |
| United States | 3 | 3% |
| Germany | 2 | 2% |
| Brazil | 1 | <1% |
| India | 1 | <1% |
| Sweden | 1 | <1% |
| Greece | 1 | <1% |
| Other | 1 | <1% |
| Unknown | 95 | 83% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 31 | 27% |
| Student > Ph. D. Student | 26 | 23% |
| Student > Master | 19 | 17% |
| Professor > Associate Professor | 7 | 6% |
| Student > Bachelor | 6 | 5% |
| Other | 15 | 13% |
| Unknown | 11 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 26 | 23% |
| Neuroscience | 18 | 16% |
| Engineering | 18 | 16% |
| Mathematics | 10 | 9% |
| Computer Science | 10 | 9% |
| Other | 15 | 13% |
| Unknown | 18 | 16% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 10 April 2019.
All research outputs
#17,286,645
of 25,374,917 outputs
Outputs from Journal of Computational Neuroscience
#181
of 329 outputs
Outputs of similar age
#33,314
of 35,889 outputs
Outputs of similar age from Journal of Computational Neuroscience
#2
of 2 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 329 research outputs from this source. They receive a mean Attention Score of 3.5. This one is in the 30th percentile – i.e., 30% of its peers scored the same or lower than it.
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 35,889 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 4th percentile – i.e., 4% of its contemporaries scored the same or lower than it.
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.