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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Equivariant 3D-conditional diffusion model for molecular linker design
|
|---|---|
| Published in |
Nature Machine Intelligence, April 2024
|
| DOI | 10.1038/s42256-024-00815-9 |
| Authors |
Ilia Igashov, Hannes Stärk, Clément Vignac, Arne Schneuing, Victor Garcia Satorras, Pascal Frossard, Max Welling, Michael Bronstein, Bruno Correia |
X Demographics
The data shown below were collected from the profiles of 63 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 | 9 | 14% |
| Switzerland | 8 | 13% |
| United Kingdom | 2 | 3% |
| Germany | 2 | 3% |
| Japan | 1 | 2% |
| Iran, Islamic Republic of | 1 | 2% |
| Singapore | 1 | 2% |
| Finland | 1 | 2% |
| Norway | 1 | 2% |
| Other | 6 | 10% |
| Unknown | 31 | 49% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 32 | 51% |
| Members of the public | 30 | 48% |
| Science communicators (journalists, bloggers, editors) | 1 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 106 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 106 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 23 | 22% |
| Researcher | 15 | 14% |
| Student > Bachelor | 7 | 7% |
| Student > Master | 6 | 6% |
| Student > Doctoral Student | 3 | 3% |
| Other | 10 | 9% |
| Unknown | 42 | 40% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 24 | 23% |
| Engineering | 8 | 8% |
| Biochemistry, Genetics and Molecular Biology | 6 | 6% |
| Chemistry | 6 | 6% |
| Unspecified | 4 | 4% |
| Other | 12 | 11% |
| Unknown | 46 | 43% |
Attention Score in Context
This research output has an Altmetric Attention Score of 35. 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 05 May 2024.
All research outputs
#1,188,133
of 25,850,376 outputs
Outputs from Nature Machine Intelligence
#305
of 781 outputs
Outputs of similar age
#12,241
of 242,506 outputs
Outputs of similar age from Nature Machine Intelligence
#11
of 27 outputs
Altmetric has tracked 25,850,376 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 781 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 66.9. This one has gotten more attention than average, scoring higher than 60% 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 242,506 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 94% of its contemporaries.
We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 59% of its contemporaries.