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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Machine learning techniques in disease forecasting: a case study on rice blast prediction
|
|---|---|
| Published in |
BMC Bioinformatics, November 2006
|
| DOI | 10.1186/1471-2105-7-485 |
| Pubmed ID | |
| Authors |
Rakesh Kaundal, Amar S Kapoor, Gajendra PS Raghava |
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 % |
|---|---|---|
| Italy | 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 260 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 3 | 1% |
| Malaysia | 1 | <1% |
| Sweden | 1 | <1% |
| Kenya | 1 | <1% |
| Israel | 1 | <1% |
| United States | 1 | <1% |
| Unknown | 252 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 53 | 20% |
| Researcher | 30 | 12% |
| Student > Master | 30 | 12% |
| Student > Bachelor | 22 | 8% |
| Professor > Associate Professor | 10 | 4% |
| Other | 47 | 18% |
| Unknown | 68 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 52 | 20% |
| Agricultural and Biological Sciences | 51 | 20% |
| Engineering | 29 | 11% |
| Biochemistry, Genetics and Molecular Biology | 11 | 4% |
| Environmental Science | 11 | 4% |
| Other | 29 | 11% |
| Unknown | 77 | 30% |
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 20 March 2018.
All research outputs
#15,495,840
of 23,028,364 outputs
Outputs from BMC Bioinformatics
#5,399
of 7,316 outputs
Outputs of similar age
#61,296
of 69,866 outputs
Outputs of similar age from BMC Bioinformatics
#50
of 62 outputs
Altmetric has tracked 23,028,364 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,316 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 18th percentile – i.e., 18% 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 69,866 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 6th percentile – i.e., 6% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 62 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.