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X Demographics
Mendeley readers
Attention Score in Context
| Title |
The Old and the New: Can Physics-Informed Deep-Learning Replace Traditional Linear Solvers?
|
|---|---|
| Published in |
Frontiers in Big Data, November 2021
|
| DOI | 10.3389/fdata.2021.669097 |
| Pubmed ID | |
| Authors |
Stefano Markidis |
X Demographics
The data shown below were collected from the profiles of 18 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 2 | 11% |
| Switzerland | 2 | 11% |
| United States | 1 | 6% |
| Ukraine | 1 | 6% |
| United Kingdom | 1 | 6% |
| Germany | 1 | 6% |
| Unknown | 10 | 56% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 17 | 94% |
| Science communicators (journalists, bloggers, editors) | 1 | 6% |
Mendeley readers
The data shown below were compiled from readership statistics for 208 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 208 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 34 | 16% |
| Researcher | 23 | 11% |
| Student > Master | 19 | 9% |
| Student > Doctoral Student | 12 | 6% |
| Student > Bachelor | 11 | 5% |
| Other | 22 | 11% |
| Unknown | 87 | 42% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 51 | 25% |
| Computer Science | 12 | 6% |
| Physics and Astronomy | 11 | 5% |
| Mathematics | 8 | 4% |
| Materials Science | 4 | 2% |
| Other | 24 | 12% |
| Unknown | 98 | 47% |
Attention Score in Context
This research output has an Altmetric Attention Score of 19. 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 26 March 2024.
All research outputs
#2,037,681
of 25,992,468 outputs
Outputs from Frontiers in Big Data
#1
of 1 outputs
Outputs of similar age
#48,275
of 524,463 outputs
Outputs of similar age from Frontiers in Big Data
#1
of 1 outputs
Altmetric has tracked 25,992,468 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.1. This one scored the same or higher as 0 of them.
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 524,463 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 90% of its contemporaries.
We're also able to compare this research output to 1 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