| Title |
Using a Bayesian hierarchical model to improve Lake Erie cyanobacteria bloom forecasts
|
|---|---|
| Published in |
Water Resources Research, October 2014
|
| DOI | 10.1002/2014wr015616 |
| Authors |
Daniel R. Obenour, Andrew D. Gronewold, Craig A. Stow, Donald Scavia |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 20% |
| United States | 1 | 20% |
| Unknown | 3 | 60% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 40% |
| Science communicators (journalists, bloggers, editors) | 2 | 40% |
| Scientists | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 134 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | <1% |
| Portugal | 1 | <1% |
| Unknown | 132 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 25 | 19% |
| Student > Master | 24 | 18% |
| Student > Ph. D. Student | 22 | 16% |
| Student > Doctoral Student | 10 | 7% |
| Student > Bachelor | 8 | 6% |
| Other | 20 | 15% |
| Unknown | 25 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Environmental Science | 42 | 31% |
| Engineering | 19 | 14% |
| Agricultural and Biological Sciences | 13 | 10% |
| Earth and Planetary Sciences | 9 | 7% |
| Economics, Econometrics and Finance | 2 | 1% |
| Other | 9 | 7% |
| Unknown | 40 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 75. 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 03 November 2014.
All research outputs
#545,232
of 24,565,648 outputs
Outputs from Water Resources Research
#83
of 5,122 outputs
Outputs of similar age
#5,736
of 260,427 outputs
Outputs of similar age from Water Resources Research
#2
of 118 outputs
Altmetric has tracked 24,565,648 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,122 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.8. 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 260,427 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 97% of its contemporaries.
We're also able to compare this research output to 118 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.