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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Machine learning models outperform deep learning models, provide interpretation and facilitate feature selection for soybean trait prediction
|
|---|---|
| Published in |
BMC Plant Biology, April 2022
|
| DOI | 10.1186/s12870-022-03559-z |
| Pubmed ID | |
| Authors |
Mitchell Gill, Robyn Anderson, Haifei Hu, Mohammed Bennamoun, Jakob Petereit, Babu Valliyodan, Henry T. Nguyen, Jacqueline Batley, Philipp E. Bayer, David Edwards |
X Demographics
The data shown below were collected from the profiles of 26 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 States | 3 | 12% |
| Germany | 2 | 8% |
| Mexico | 2 | 8% |
| United Kingdom | 2 | 8% |
| Australia | 2 | 8% |
| Austria | 1 | 4% |
| India | 1 | 4% |
| Switzerland | 1 | 4% |
| Unknown | 12 | 46% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 19 | 73% |
| Scientists | 5 | 19% |
| Practitioners (doctors, other healthcare professionals) | 2 | 8% |
Mendeley readers
The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 53 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 17% |
| Student > Master | 7 | 13% |
| Researcher | 7 | 13% |
| Student > Bachelor | 2 | 4% |
| Lecturer | 2 | 4% |
| Other | 2 | 4% |
| Unknown | 24 | 45% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 15 | 28% |
| Computer Science | 8 | 15% |
| Biochemistry, Genetics and Molecular Biology | 3 | 6% |
| Engineering | 2 | 4% |
| Neuroscience | 1 | 2% |
| Other | 1 | 2% |
| Unknown | 23 | 43% |
Attention Score in Context
This research output has an Altmetric Attention Score of 14. 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 01 July 2022.
All research outputs
#2,636,532
of 25,353,525 outputs
Outputs from BMC Plant Biology
#124
of 3,580 outputs
Outputs of similar age
#58,835
of 438,386 outputs
Outputs of similar age from BMC Plant Biology
#3
of 111 outputs
Altmetric has tracked 25,353,525 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,580 research outputs from this source. They receive a mean Attention Score of 3.0. This one has done particularly well, scoring higher than 96% of its peers.
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 438,386 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 111 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.