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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Using hyperspectral analysis as a potential high throughput phenotyping tool in GWAS for protein content of rice quality
|
|---|---|
| Published in |
Plant Methods, May 2019
|
| DOI | 10.1186/s13007-019-0432-x |
| Pubmed ID | |
| Authors |
Dawei Sun, Haiyan Cen, Haiyong Weng, Liang Wan, Alwaseela Abdalla, Ahmed Islam El-Manawy, Yueming Zhu, Nan Zhao, Haowei Fu, Juan Tang, Xiaolong Li, Hongkun Zheng, Qingyao Shu, Fei Liu, Yong He |
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 % |
|---|---|---|
| Switzerland | 1 | 33% |
| United Kingdom | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 33% |
| Members of the public | 1 | 33% |
| Science communicators (journalists, bloggers, editors) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 95 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 95 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 12 | 13% |
| Researcher | 11 | 12% |
| Student > Master | 8 | 8% |
| Student > Doctoral Student | 8 | 8% |
| Student > Bachelor | 7 | 7% |
| Other | 15 | 16% |
| Unknown | 34 | 36% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 45 | 47% |
| Biochemistry, Genetics and Molecular Biology | 5 | 5% |
| Engineering | 4 | 4% |
| Chemistry | 2 | 2% |
| Business, Management and Accounting | 1 | 1% |
| Other | 6 | 6% |
| Unknown | 32 | 34% |
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 04 June 2019.
All research outputs
#14,450,741
of 23,148,322 outputs
Outputs from Plant Methods
#724
of 1,096 outputs
Outputs of similar age
#192,360
of 350,284 outputs
Outputs of similar age from Plant Methods
#20
of 32 outputs
Altmetric has tracked 23,148,322 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 1,096 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 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 350,284 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 32 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.