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X Demographics
Mendeley readers
Attention Score in Context
Title |
Explainable and Interpretable Models in Computer Vision and Machine Learning
|
---|---|
Published by |
arXiv, January 2018
|
DOI | 10.1007/978-3-319-98131-4 |
ISBNs |
978-3-31-998130-7, 978-3-31-998131-4
|
Authors |
Olivier Goudet, Diviyan Kalainathan, Philippe Caillou, David Lopez-Paz, Isabelle Guyon, Michèle Sebag, Aris Tritas, Paola Tubaro |
Editors |
Hugo Jair Escalante, Sergio Escalera, Isabelle Guyon, Xavier Baró, Yağmur Güçlütürk, Umut Güçlü, Marcel van Gerven |
X Demographics
The data shown below were collected from the profiles of 58 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Mexico | 9 | 16% |
United States | 8 | 14% |
United Kingdom | 4 | 7% |
Singapore | 2 | 3% |
Italy | 2 | 3% |
Switzerland | 2 | 3% |
France | 1 | 2% |
Germany | 1 | 2% |
Japan | 1 | 2% |
Other | 2 | 3% |
Unknown | 26 | 45% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 37 | 64% |
Scientists | 18 | 31% |
Science communicators (journalists, bloggers, editors) | 3 | 5% |
Mendeley readers
The data shown below were compiled from readership statistics for 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 57 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 69 | 121% |
Student > Master | 42 | 74% |
Researcher | 34 | 60% |
Student > Bachelor | 17 | 30% |
Student > Doctoral Student | 11 | 19% |
Other | 30 | 53% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 125 | 219% |
Engineering | 21 | 37% |
Mathematics | 12 | 21% |
Economics, Econometrics and Finance | 8 | 14% |
Chemistry | 4 | 7% |
Other | 28 | 49% |
Attention Score in Context
This research output has an Altmetric Attention Score of 55. 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 21 March 2024.
All research outputs
#784,737
of 25,605,018 outputs
Outputs from arXiv
#10,074
of 931,742 outputs
Outputs of similar age
#17,842
of 451,009 outputs
Outputs of similar age from arXiv
#237
of 17,260 outputs
Altmetric has tracked 25,605,018 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 931,742 research outputs from this source. They receive a mean Attention Score of 4.3. 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 451,009 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 96% of its contemporaries.
We're also able to compare this research output to 17,260 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.