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Bayesian Hierarchical Models can Infer Interpretable Predictions of Leaf Area Index From Heterogeneous Datasets

Overview of attention for article published in Frontiers in Environmental Science, January 2022
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About this Attention Score

  • Good Attention Score compared to outputs of the same age and source (73rd percentile)

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2 X users

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mendeley
13 Mendeley
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Title
Bayesian Hierarchical Models can Infer Interpretable Predictions of Leaf Area Index From Heterogeneous Datasets
Published in
Frontiers in Environmental Science, January 2022
DOI 10.3389/fenvs.2021.780814
Authors

Olivera Stojanović, Bastian Siegmann, Thomas Jarmer, Gordon Pipa, Johannes Leugering

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 15%
Researcher 1 8%
Student > Postgraduate 1 8%
Unknown 9 69%
Readers by discipline Count As %
Chemical Engineering 1 8%
Environmental Science 1 8%
Agricultural and Biological Sciences 1 8%
Earth and Planetary Sciences 1 8%
Unknown 9 69%
Attention Score in Context

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 12 January 2022.
All research outputs
#18,866,295
of 24,049,457 outputs
Outputs from Frontiers in Environmental Science
#1,404
of 4,082 outputs
Outputs of similar age
#357,206
of 508,314 outputs
Outputs of similar age from Frontiers in Environmental Science
#76
of 310 outputs
Altmetric has tracked 24,049,457 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,082 research outputs from this source. They receive a mean Attention Score of 4.4. This one has gotten more attention than average, scoring higher than 62% 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 508,314 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 310 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 73% of its contemporaries.