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Timeline
X Demographics
Mendeley readers
Attention Score in Context
Title |
AutoML-GWL: Automated machine learning model for the prediction of groundwater level
|
---|---|
Published in |
Engineering Applications of Artificial Intelligence, January 2024
|
DOI | 10.1016/j.engappai.2023.107405 |
Authors |
Abhilash Singh, Sharad Patel, Vipul Bhadani, Vaibhav Kumar, Kumar Gaurav |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
India | 6 | 21% |
United Kingdom | 2 | 7% |
Morocco | 1 | 3% |
South Africa | 1 | 3% |
Greece | 1 | 3% |
Indonesia | 1 | 3% |
Ecuador | 1 | 3% |
United States | 1 | 3% |
Belize | 1 | 3% |
Other | 1 | 3% |
Unknown | 13 | 45% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 23 | 79% |
Scientists | 5 | 17% |
Science communicators (journalists, bloggers, editors) | 1 | 3% |
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 | 5 | 10% |
Researcher | 4 | 8% |
Student > Master | 4 | 8% |
Student > Doctoral Student | 3 | 6% |
Other | 2 | 4% |
Other | 7 | 14% |
Unknown | 25 | 50% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 7 | 14% |
Engineering | 7 | 14% |
Arts and Humanities | 2 | 4% |
Agricultural and Biological Sciences | 2 | 4% |
Environmental Science | 2 | 4% |
Other | 2 | 4% |
Unknown | 28 | 56% |
Attention Score in Context
This research output has an Altmetric Attention Score of 18. 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 03 January 2024.
All research outputs
#2,180,276
of 26,794,105 outputs
Outputs from Engineering Applications of Artificial Intelligence
#18
of 887 outputs
Outputs of similar age
#35,899
of 395,926 outputs
Outputs of similar age from Engineering Applications of Artificial Intelligence
#1
of 24 outputs
Altmetric has tracked 26,794,105 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 887 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done particularly well, scoring higher than 97% 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 395,926 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 24 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 95% of its contemporaries.