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X Demographics
Mendeley readers
Attention Score in Context
Chapter title |
TADPOLE Challenge: Accurate Alzheimer’s Disease Prediction Through Crowdsourced Forecasting of Future Data
|
---|---|
Chapter number | 1 |
Book title |
Predictive Intelligence in Medicine
|
Published in |
arXiv, October 2019
|
DOI | 10.1007/978-3-030-32281-6_1 |
Pubmed ID | |
Book ISBNs |
978-3-03-032280-9, 978-3-03-032281-6
|
Authors |
Răzvan V. Marinescu, Neil P. Oxtoby, Alexandra L. Young, Esther E. Bron, Arthur W. Toga, Michael W. Weiner, Frederik Barkhof, Nick C. Fox, Polina Golland, Stefan Klein, Daniel C. Alexander, Razvan V. Marinescu, Marinescu, Răzvan V., Oxtoby, Neil P., Young, Alexandra L., Bron, Esther E., Toga, Arthur W., Weiner, Michael W., Barkhof, Frederik, Fox, Nick C., Golland, Polina, Klein, Stefan, Alexander, Daniel C., Marinescu, RV, Oxtoby, NP, Young, AL, Bron, EE, Toga, AW, Weiner, MW, Barkhof, F, Fox, NC, Golland, P, Klein, S, Alexander, DC |
X Demographics
The data shown below were collected from the profiles of 4 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 | 1 | 25% |
Unknown | 3 | 75% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 4 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 41 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 9 | 22% |
Researcher | 5 | 12% |
Other | 3 | 7% |
Student > Master | 2 | 5% |
Professor | 1 | 2% |
Other | 1 | 2% |
Unknown | 20 | 49% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 7 | 17% |
Neuroscience | 4 | 10% |
Medicine and Dentistry | 3 | 7% |
Engineering | 2 | 5% |
Mathematics | 2 | 5% |
Other | 1 | 2% |
Unknown | 22 | 54% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 14 January 2021.
All research outputs
#2,999,754
of 23,168,000 outputs
Outputs from arXiv
#55,399
of 953,740 outputs
Outputs of similar age
#65,207
of 354,133 outputs
Outputs of similar age from arXiv
#1,891
of 29,311 outputs
Altmetric has tracked 23,168,000 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 953,740 research outputs from this source. They receive a mean Attention Score of 3.9. This one has done particularly well, scoring higher than 94% 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 354,133 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 81% of its contemporaries.
We're also able to compare this research output to 29,311 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 93% of its contemporaries.