↓ Skip to main content

Opportunities and limitations of the ChatGPT Advanced Data Analysis plugin for hydrological analyses

Overview of attention for article published in Hydrological Processes, October 2023
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#41 of 2,075)
  • High Attention Score compared to outputs of the same age (94th percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

Mentioned by

news
3 news outlets
twitter
23 X users

Readers on

mendeley
16 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
Opportunities and limitations of the ChatGPT Advanced Data Analysis plugin for hydrological analyses
Published in
Hydrological Processes, October 2023
DOI 10.1002/hyp.15015
Authors

Dylan J. Irvine, Landon J. S. Halloran, Philip Brunner

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 23 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 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Other 3 19%
Student > Ph. D. Student 2 13%
Librarian 1 6%
Lecturer > Senior Lecturer 1 6%
Professor 1 6%
Other 4 25%
Unknown 4 25%
Readers by discipline Count As %
Earth and Planetary Sciences 3 19%
Agricultural and Biological Sciences 2 13%
Environmental Science 2 13%
Engineering 2 13%
Computer Science 1 6%
Other 3 19%
Unknown 3 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 37. 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 October 2023.
All research outputs
#1,092,462
of 25,247,084 outputs
Outputs from Hydrological Processes
#41
of 2,075 outputs
Outputs of similar age
#18,112
of 348,832 outputs
Outputs of similar age from Hydrological Processes
#3
of 15 outputs
Altmetric has tracked 25,247,084 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,075 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done particularly well, scoring higher than 98% 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 348,832 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 94% of its contemporaries.
We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.