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A Mechanical Model for Sieving of Large Deposited Atmospheric Particulates in Surface Soil

Overview of attention for article published in Environmental Modeling & Assessment, July 2018
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2 X users

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mendeley
3 Mendeley
Title
A Mechanical Model for Sieving of Large Deposited Atmospheric Particulates in Surface Soil
Published in
Environmental Modeling & Assessment, July 2018
DOI 10.1007/s10666-018-9629-z
Authors

Masashi Nakano, Raymond N. Yong

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 1 33%
Student > Doctoral Student 1 33%
Unknown 1 33%
Readers by discipline Count As %
Linguistics 1 33%
Unknown 2 67%
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 11 November 2019.
All research outputs
#18,697,497
of 23,172,045 outputs
Outputs from Environmental Modeling & Assessment
#127
of 148 outputs
Outputs of similar age
#253,290
of 329,072 outputs
Outputs of similar age from Environmental Modeling & Assessment
#2
of 3 outputs
Altmetric has tracked 23,172,045 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 148 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.2. This one is in the 7th percentile – i.e., 7% of its peers scored the same or lower than it.
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 329,072 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.