You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Hyperspectral band selection using genetic algorithm and support vector machines for early identification of charcoal rot disease in soybean stems
|
|---|---|
| Published in |
Plant Methods, October 2018
|
| DOI | 10.1186/s13007-018-0349-9 |
| Pubmed ID | |
| Authors |
Koushik Nagasubramanian, Sarah Jones, Soumik Sarkar, Asheesh K. Singh, Arti Singh, Baskar Ganapathysubramanian |
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 Kingdom | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Science communicators (journalists, bloggers, editors) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 120 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 120 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 23 | 19% |
| Student > Master | 17 | 14% |
| Researcher | 11 | 9% |
| Other | 8 | 7% |
| Student > Bachelor | 7 | 6% |
| Other | 12 | 10% |
| Unknown | 42 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 27 | 23% |
| Engineering | 15 | 13% |
| Computer Science | 12 | 10% |
| Mathematics | 3 | 3% |
| Business, Management and Accounting | 2 | 2% |
| Other | 11 | 9% |
| Unknown | 50 | 42% |
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 2018.
All research outputs
#14,141,707
of 23,105,443 outputs
Outputs from Plant Methods
#685
of 1,094 outputs
Outputs of similar age
#184,224
of 344,075 outputs
Outputs of similar age from Plant Methods
#16
of 34 outputs
Altmetric has tracked 23,105,443 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 1,094 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one is in the 34th percentile – i.e., 34% 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 344,075 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 34 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.