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X Demographics
Mendeley readers
Attention Score in Context
| Title |
The gene normalization task in BioCreative III
|
|---|---|
| Published in |
BMC Bioinformatics, October 2011
|
| DOI | 10.1186/1471-2105-12-s8-s2 |
| Pubmed ID | |
| Authors |
Zhiyong Lu, Hung-Yu Kao, Chih-Hsuan Wei, Minlie Huang, Jingchen Liu, Cheng-Ju Kuo, Chun-Nan Hsu, Richard Tzong-Han Tsai, Hong-Jie Dai, Naoaki Okazaki, Han-Cheol Cho, Martin Gerner, Illes Solt, Shashank Agarwal, Feifan Liu, Dina Vishnyakova, Patrick Ruch, Martin Romacker, Fabio Rinaldi, Sanmitra Bhattacharya, Padmini Srinivasan, Hongfang Liu, Manabu Torii, Sergio Matos, David Campos, Karin Verspoor, Kevin M Livingston, W John Wilbur |
| Abstract |
We report the Gene Normalization (GN) challenge in BioCreative III where participating teams were asked to return a ranked list of identifiers of the genes detected in full-text articles. For training, 32 fully and 500 partially annotated articles were prepared. A total of 507 articles were selected as the test set. Due to the high annotation cost, it was not feasible to obtain gold-standard human annotations for all test articles. Instead, we developed an Expectation Maximization (EM) algorithm approach for choosing a small number of test articles for manual annotation that were most capable of differentiating team performance. Moreover, the same algorithm was subsequently used for inferring ground truth based solely on team submissions. We report team performance on both gold standard and inferred ground truth using a newly proposed metric called Threshold Average Precision (TAP-k). |
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 % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 4% |
| Spain | 2 | 3% |
| Netherlands | 1 | 1% |
| Portugal | 1 | 1% |
| Germany | 1 | 1% |
| Australia | 1 | 1% |
| Unknown | 66 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 16 | 21% |
| Researcher | 15 | 20% |
| Student > Master | 11 | 15% |
| Professor > Associate Professor | 6 | 8% |
| Student > Bachelor | 6 | 8% |
| Other | 11 | 15% |
| Unknown | 10 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 35 | 47% |
| Agricultural and Biological Sciences | 12 | 16% |
| Biochemistry, Genetics and Molecular Biology | 3 | 4% |
| Linguistics | 2 | 3% |
| Engineering | 2 | 3% |
| Other | 8 | 11% |
| Unknown | 13 | 17% |
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 31 August 2012.
All research outputs
#14,137,641
of 22,653,392 outputs
Outputs from BMC Bioinformatics
#4,706
of 7,236 outputs
Outputs of similar age
#86,662
of 132,696 outputs
Outputs of similar age from BMC Bioinformatics
#57
of 83 outputs
Altmetric has tracked 22,653,392 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,236 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. 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 132,696 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 83 others from the same source and published within six weeks on either side of this one. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.