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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Generative Models for Automatic Chemical Design
|
|---|---|
| Chapter number | 21 |
| Book title |
Machine Learning Meets Quantum Physics
|
| Published in |
arXiv, January 2020
|
| DOI | 10.1007/978-3-030-40245-7_21 |
| Book ISBNs |
978-3-03-040244-0, 978-3-03-040245-7
|
| Authors |
Daniel Schwalbe-Koda, Rafael Gómez-Bombarelli |
X Demographics
The data shown below were collected from the profiles of 139 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 36 | 26% |
| United States | 9 | 6% |
| Canada | 4 | 3% |
| India | 2 | 1% |
| France | 2 | 1% |
| Finland | 1 | <1% |
| China | 1 | <1% |
| Switzerland | 1 | <1% |
| Italy | 1 | <1% |
| Other | 7 | 5% |
| Unknown | 75 | 54% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 108 | 78% |
| Scientists | 29 | 21% |
| Science communicators (journalists, bloggers, editors) | 1 | <1% |
| Practitioners (doctors, other healthcare professionals) | 1 | <1% |
Mendeley readers
The data shown below were compiled from readership statistics for 180 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 180 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 44 | 24% |
| Student > Ph. D. Student | 31 | 17% |
| Student > Master | 16 | 9% |
| Student > Bachelor | 13 | 7% |
| Other | 11 | 6% |
| Other | 17 | 9% |
| Unknown | 48 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 35 | 19% |
| Computer Science | 31 | 17% |
| Materials Science | 14 | 8% |
| Engineering | 10 | 6% |
| Physics and Astronomy | 7 | 4% |
| Other | 27 | 15% |
| Unknown | 56 | 31% |
Attention Score in Context
This research output has an Altmetric Attention Score of 77. 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 25 June 2021.
All research outputs
#564,781
of 25,768,270 outputs
Outputs from arXiv
#6,817
of 942,654 outputs
Outputs of similar age
#13,784
of 480,048 outputs
Outputs of similar age from arXiv
#171
of 20,926 outputs
Altmetric has tracked 25,768,270 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 942,654 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done particularly well, scoring higher than 99% 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 480,048 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 20,926 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 99% of its contemporaries.