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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Knowledge elicitation via sequential probabilistic inference for high-dimensional prediction
|
|---|---|
| Published in |
Machine Learning, July 2017
|
| DOI | 10.1007/s10994-017-5651-7 |
| Authors |
Pedram Daee, Tomi Peltola, Marta Soare, Samuel Kaski |
X Demographics
The data shown below were collected from the profiles of 16 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 25% |
| Finland | 2 | 13% |
| Germany | 1 | 6% |
| Unknown | 9 | 56% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 11 | 69% |
| Scientists | 3 | 19% |
| Science communicators (journalists, bloggers, editors) | 2 | 13% |
Mendeley readers
The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 48 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 9 | 19% |
| Student > Ph. D. Student | 7 | 15% |
| Student > Doctoral Student | 5 | 10% |
| Researcher | 5 | 10% |
| Student > Postgraduate | 2 | 4% |
| Other | 4 | 8% |
| Unknown | 16 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 18 | 38% |
| Engineering | 3 | 6% |
| Agricultural and Biological Sciences | 2 | 4% |
| Mathematics | 1 | 2% |
| Nursing and Health Professions | 1 | 2% |
| Other | 6 | 13% |
| Unknown | 17 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 January 2021.
All research outputs
#4,186,990
of 24,998,746 outputs
Outputs from Machine Learning
#108
of 1,152 outputs
Outputs of similar age
#68,170
of 317,670 outputs
Outputs of similar age from Machine Learning
#2
of 10 outputs
Altmetric has tracked 24,998,746 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,152 research outputs from this source. They receive a mean Attention Score of 4.1. This one has done particularly well, scoring higher than 90% 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 317,670 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 78% of its contemporaries.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 8 of them.