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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A comparison of machine learning algorithms for chemical toxicity classification using a simulated multi-scale data model
|
|---|---|
| Published in |
BMC Bioinformatics, May 2008
|
| DOI | 10.1186/1471-2105-9-241 |
| Pubmed ID | |
| Authors |
Richard Judson, Fathi Elloumi, R Woodrow Setzer, Zhen Li, Imran Shah |
X Demographics
The data shown below were collected from the profiles of 21 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 | 8 | 38% |
| Spain | 2 | 10% |
| India | 2 | 10% |
| Ecuador | 1 | 5% |
| Mexico | 1 | 5% |
| Chile | 1 | 5% |
| Unknown | 6 | 29% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 14 | 67% |
| Scientists | 7 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 108 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 2% |
| Sweden | 1 | <1% |
| Argentina | 1 | <1% |
| Australia | 1 | <1% |
| Unknown | 103 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 26 | 24% |
| Researcher | 20 | 19% |
| Student > Master | 11 | 10% |
| Other | 7 | 6% |
| Student > Bachelor | 6 | 6% |
| Other | 22 | 20% |
| Unknown | 16 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 25 | 23% |
| Computer Science | 18 | 17% |
| Chemistry | 10 | 9% |
| Biochemistry, Genetics and Molecular Biology | 8 | 7% |
| Medicine and Dentistry | 7 | 6% |
| Other | 19 | 18% |
| Unknown | 21 | 19% |
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 15 December 2017.
All research outputs
#2,723,524
of 24,998,746 outputs
Outputs from BMC Bioinformatics
#780
of 7,630 outputs
Outputs of similar age
#7,671
of 92,265 outputs
Outputs of similar age from BMC Bioinformatics
#5
of 49 outputs
Altmetric has tracked 24,998,746 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 7,630 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done well, scoring higher than 89% 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 92,265 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 49 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 91% of its contemporaries.