The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Deep Learning Techniques to Improve the Performance of Olive Oil Classification
|
|---|---|
| Published in |
Frontiers in Chemistry, January 2020
|
| DOI | 10.3389/fchem.2019.00929 |
| Pubmed ID | |
| Authors |
Belén Vega-Márquez, Isabel Nepomuceno-Chamorro, Natividad Jurado-Campos, Cristina Rubio-Escudero |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| South Africa | 1 | 25% |
| Unknown | 3 | 75% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 50% |
| Science communicators (journalists, bloggers, editors) | 1 | 25% |
| Members of the public | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 50 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 22% |
| Student > Master | 8 | 16% |
| Professor > Associate Professor | 3 | 6% |
| Student > Bachelor | 2 | 4% |
| Lecturer | 2 | 4% |
| Other | 6 | 12% |
| Unknown | 18 | 36% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 7 | 14% |
| Computer Science | 5 | 10% |
| Chemistry | 5 | 10% |
| Agricultural and Biological Sciences | 4 | 8% |
| Business, Management and Accounting | 2 | 4% |
| Other | 6 | 12% |
| Unknown | 21 | 42% |
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 29 July 2022.
All research outputs
#15,840,257
of 23,538,320 outputs
Outputs from Frontiers in Chemistry
#1,633
of 6,188 outputs
Outputs of similar age
#276,903
of 458,144 outputs
Outputs of similar age from Frontiers in Chemistry
#70
of 261 outputs
Altmetric has tracked 23,538,320 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 6,188 research outputs from this source. They receive a mean Attention Score of 2.1. This one has gotten more attention than average, scoring higher than 71% 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 458,144 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 261 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 72% of its contemporaries.