| Title |
Modeling subjective belief states in computational psychiatry: interoceptive inference as a candidate framework
|
|---|---|
| Published in |
Psychopharmacology, June 2019
|
| DOI | 10.1007/s00213-019-05300-5 |
| Pubmed ID | |
| Authors |
Xiaosi Gu, Thomas H. B. FitzGerald, Karl J. Friston |
X Demographics
The data shown below were collected from the profiles of 41 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 | 6 | 15% |
| United Kingdom | 5 | 12% |
| Australia | 2 | 5% |
| Switzerland | 1 | 2% |
| Denmark | 1 | 2% |
| Italy | 1 | 2% |
| Japan | 1 | 2% |
| Israel | 1 | 2% |
| Korea, Republic of | 1 | 2% |
| Other | 2 | 5% |
| Unknown | 20 | 49% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 22 | 54% |
| Scientists | 16 | 39% |
| Practitioners (doctors, other healthcare professionals) | 2 | 5% |
| Science communicators (journalists, bloggers, editors) | 1 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 107 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 107 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 21 | 20% |
| Student > Ph. D. Student | 19 | 18% |
| Researcher | 16 | 15% |
| Student > Master | 11 | 10% |
| Student > Doctoral Student | 6 | 6% |
| Other | 13 | 12% |
| Unknown | 21 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 32 | 30% |
| Neuroscience | 20 | 19% |
| Medicine and Dentistry | 11 | 10% |
| Nursing and Health Professions | 4 | 4% |
| Agricultural and Biological Sciences | 3 | 3% |
| Other | 10 | 9% |
| Unknown | 27 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 23. 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 02 August 2022.
All research outputs
#1,643,555
of 25,260,058 outputs
Outputs from Psychopharmacology
#400
of 5,643 outputs
Outputs of similar age
#34,710
of 358,369 outputs
Outputs of similar age from Psychopharmacology
#10
of 58 outputs
Altmetric has tracked 25,260,058 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,643 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.5. 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 358,369 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 58 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.