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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Mechanisms underlying the predictive power of high skeletal muscle uptake of FDG in amyotrophic lateral sclerosis
|
|---|---|
| Published in |
EJNMMI Research, July 2020
|
| DOI | 10.1186/s13550-020-00666-6 |
| Pubmed ID | |
| Authors |
Cecilia Marini, Vanessa Cossu, Tiziana Bonifacino, Matteo Bauckneht, Carola Torazza, Silvia Bruno, Patrizia Castellani, Silvia Ravera, Marco Milanese, Consuelo Venturi, Sebastiano Carlone, Patrizia Piccioli, Laura Emionite, Silvia Morbelli, Anna Maria Orengo, Maria Isabella Donegani, Alberto Miceli, Stefano Raffa, Stefano Marra, Alessio Signori, Katia Cortese, Federica Grillo, Roberto Fiocca, Giambattista Bonanno, Gianmario Sambuceti |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 23 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 26% |
| Student > Master | 4 | 17% |
| Student > Doctoral Student | 1 | 4% |
| Student > Ph. D. Student | 1 | 4% |
| Student > Bachelor | 1 | 4% |
| Other | 2 | 9% |
| Unknown | 8 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 5 | 22% |
| Medicine and Dentistry | 3 | 13% |
| Biochemistry, Genetics and Molecular Biology | 2 | 9% |
| Linguistics | 1 | 4% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 10 | 43% |
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 10 July 2020.
All research outputs
#3,270,435
of 23,220,133 outputs
Outputs from EJNMMI Research
#32
of 568 outputs
Outputs of similar age
#85,651
of 397,131 outputs
Outputs of similar age from EJNMMI Research
#4
of 25 outputs
Altmetric has tracked 23,220,133 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 568 research outputs from this source. They receive a mean Attention Score of 2.5. This one has done particularly well, scoring higher than 92% 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 397,131 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 78% of its contemporaries.
We're also able to compare this research output to 25 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.