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Time-Lagged Prediction of Food Craving With Qualitative Distinct Predictor Types: An Application of BISCWIT

Overview of attention for article published in Frontiers in Digital Health, September 2021
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (64th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
6 X users

Citations

dimensions_citation
6 Dimensions

Readers on

mendeley
6 Mendeley
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Title
Time-Lagged Prediction of Food Craving With Qualitative Distinct Predictor Types: An Application of BISCWIT
Published in
Frontiers in Digital Health, September 2021
DOI 10.3389/fdgth.2021.694233
Authors

Tim Kaiser, Björn Butter, Samuel Arzt, Björn Pannicke, Julia Reichenberger, Simon Ginzinger, Jens Blechert

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 2 33%
Researcher 1 17%
Unknown 3 50%
Readers by discipline Count As %
Unspecified 2 33%
Psychology 1 17%
Unknown 3 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 October 2021.
All research outputs
#8,050,146
of 25,080,267 outputs
Outputs from Frontiers in Digital Health
#302
of 776 outputs
Outputs of similar age
#151,121
of 426,703 outputs
Outputs of similar age from Frontiers in Digital Health
#33
of 63 outputs
Altmetric has tracked 25,080,267 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 776 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.4. This one has gotten more attention than average, scoring higher than 59% 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 426,703 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 64% of its contemporaries.
We're also able to compare this research output to 63 others from the same source and published within six weeks on either side of this one. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.