↓ Skip to main content

SalaciaML: A Deep Learning Approach for Supporting Ocean Data Quality Control

Overview of attention for article published in Frontiers in Marine Science, April 2021
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (56th percentile)

Mentioned by

twitter
9 X users

Citations

dimensions_citation
16 Dimensions

Readers on

mendeley
22 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
SalaciaML: A Deep Learning Approach for Supporting Ocean Data Quality Control
Published in
Frontiers in Marine Science, April 2021
DOI 10.3389/fmars.2021.611742
Authors

Sebastian Mieruch, Serdar Demirel, Simona Simoncelli, Reiner Schlitzer, Steffen Seitz

X Demographics

X Demographics

The data shown below were collected from the profiles of 9 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 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 22 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 18%
Student > Ph. D. Student 3 14%
Researcher 3 14%
Professor > Associate Professor 2 9%
Unknown 10 45%
Readers by discipline Count As %
Earth and Planetary Sciences 6 27%
Computer Science 3 14%
Engineering 2 9%
Physics and Astronomy 1 5%
Unknown 10 45%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 14 May 2021.
All research outputs
#5,568,746
of 26,382,745 outputs
Outputs from Frontiers in Marine Science
#3,273
of 11,362 outputs
Outputs of similar age
#125,713
of 459,215 outputs
Outputs of similar age from Frontiers in Marine Science
#195
of 453 outputs
Altmetric has tracked 26,382,745 research outputs across all sources so far. Compared to these this one has done well and is in the 78th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,362 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.6. 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 459,215 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 72% of its contemporaries.
We're also able to compare this research output to 453 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 56% of its contemporaries.