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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Exploiting in silico modelling to enhance translation of liver cell therapies from bench to bedside
|
|---|---|
| Published in |
npj Regenerative Medicine, May 2024
|
| DOI | 10.1038/s41536-024-00361-3 |
| Pubmed ID | |
| Authors |
Candice Ashmore-Harris, Evangelia Antonopoulou, Simon M. Finney, Melissa R. Vieira, Matthew G. Hennessy, Andreas Muench, Wei-Yu Lu, Victoria L. Gadd, Alicia J. El Haj, Stuart J. Forbes, Sarah L. Waters |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 3 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Science communicators (journalists, bloggers, editors) | 1 | 33% |
| Scientists | 1 | 33% |
| Practitioners (doctors, other healthcare professionals) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 1 | 100% |
| Readers by discipline | Count | As % |
|---|---|---|
| Nursing and Health Professions | 1 | 100% |
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 09 May 2024.
All research outputs
#3,705,826
of 25,877,363 outputs
Outputs from npj Regenerative Medicine
#145
of 332 outputs
Outputs of similar age
#21,029
of 151,832 outputs
Outputs of similar age from npj Regenerative Medicine
#1
of 6 outputs
Altmetric has tracked 25,877,363 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 332 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.0. This one has gotten more attention than average, scoring higher than 56% 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 151,832 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 86% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them