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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Benchmarking infrastructure for mutation text mining
|
|---|---|
| Published in |
Journal of Biomedical Semantics, February 2014
|
| DOI | 10.1186/2041-1480-5-11 |
| Pubmed ID | |
| Authors |
Artjom Klein, Alexandre Riazanov, Matthew M Hindle, Christopher JO Baker |
| Abstract |
Experimental research on the automatic extraction of information about mutations from texts is greatly hindered by the lack of consensus evaluation infrastructure for the testing and benchmarking of mutation text mining systems. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 50% |
| Canada | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 2 | 3% |
| Netherlands | 1 | 2% |
| Canada | 1 | 2% |
| Mexico | 1 | 2% |
| Belgium | 1 | 2% |
| Croatia | 1 | 2% |
| Unknown | 51 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 19% |
| Researcher | 11 | 19% |
| Student > Master | 6 | 10% |
| Student > Doctoral Student | 5 | 9% |
| Student > Bachelor | 3 | 5% |
| Other | 11 | 19% |
| Unknown | 11 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 18 | 31% |
| Agricultural and Biological Sciences | 12 | 21% |
| Engineering | 6 | 10% |
| Linguistics | 2 | 3% |
| Arts and Humanities | 2 | 3% |
| Other | 7 | 12% |
| Unknown | 11 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 12 October 2019.
All research outputs
#15,516,483
of 25,371,288 outputs
Outputs from Journal of Biomedical Semantics
#210
of 368 outputs
Outputs of similar age
#123,525
of 234,818 outputs
Outputs of similar age from Journal of Biomedical Semantics
#7
of 10 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 368 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 42nd percentile – i.e., 42% 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 234,818 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.