↓ Skip to main content

Prediction of the Minimum Film Boiling Temperature of Quenching Vertical Rods in Water Using Random Forest Machine Learning Algorithm

Overview of attention for article published in Frontiers in Energy Research, April 2021
Altmetric Badge

About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (51st percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

twitter
5 X users

Citations

dimensions_citation
11 Dimensions

Readers on

mendeley
19 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Prediction of the Minimum Film Boiling Temperature of Quenching Vertical Rods in Water Using Random Forest Machine Learning Algorithm
Published in
Frontiers in Energy Research, April 2021
DOI 10.3389/fenrg.2021.668227
Authors

Sorour Alotaibi, Shikha Ebrahim, Ayed Salman

Timeline

Login to access the full chart related to this output.

If you don’t have an account, click here to discover Explorer

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 19 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 26%
Other 2 11%
Researcher 1 5%
Lecturer > Senior Lecturer 1 5%
Unknown 10 53%
Readers by discipline Count As %
Economics, Econometrics and Finance 5 26%
Business, Management and Accounting 1 5%
Sports and Recreations 1 5%
Physics and Astronomy 1 5%
Engineering 1 5%
Other 0 0%
Unknown 10 53%
Attention Score in Context

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 28 April 2021.
All research outputs
#13,745,087
of 23,302,246 outputs
Outputs from Frontiers in Energy Research
#323
of 3,443 outputs
Outputs of similar age
#204,917
of 437,380 outputs
Outputs of similar age from Frontiers in Energy Research
#25
of 211 outputs
Altmetric has tracked 23,302,246 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,443 research outputs from this source. They receive a mean Attention Score of 1.7. This one has done particularly well, scoring higher than 90% 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 437,380 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.
We're also able to compare this research output to 211 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.