| Title |
Decomposing the effects of context valence and feedback information on speed and accuracy during reinforcement learning: a meta-analytical approach using diffusion decision modeling
|
|---|---|
| Published in |
Cognitive, Affective, & Behavioral Neuroscience, June 2019
|
| DOI | 10.3758/s13415-019-00723-1 |
| Pubmed ID | |
| Authors |
Laura Fontanesi, Stefano Palminteri, Maël Lebreton |
X Demographics
The data shown below were collected from the profiles of 15 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 4 | 27% |
| United Kingdom | 3 | 20% |
| Switzerland | 1 | 7% |
| Israel | 1 | 7% |
| Denmark | 1 | 7% |
| Japan | 1 | 7% |
| China | 1 | 7% |
| Unknown | 3 | 20% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 9 | 60% |
| Scientists | 5 | 33% |
| Practitioners (doctors, other healthcare professionals) | 1 | 7% |
Mendeley readers
The data shown below were compiled from readership statistics for 85 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 85 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 22 | 26% |
| Student > Ph. D. Student | 13 | 15% |
| Researcher | 7 | 8% |
| Student > Bachelor | 6 | 7% |
| Student > Postgraduate | 5 | 6% |
| Other | 11 | 13% |
| Unknown | 21 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 23 | 27% |
| Neuroscience | 15 | 18% |
| Agricultural and Biological Sciences | 4 | 5% |
| Computer Science | 3 | 4% |
| Engineering | 2 | 2% |
| Other | 9 | 11% |
| Unknown | 29 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 13 January 2022.
All research outputs
#3,920,820
of 24,003,070 outputs
Outputs from Cognitive, Affective, & Behavioral Neuroscience
#176
of 974 outputs
Outputs of similar age
#76,830
of 356,609 outputs
Outputs of similar age from Cognitive, Affective, & Behavioral Neuroscience
#5
of 17 outputs
Altmetric has tracked 24,003,070 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 974 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.4. This one has done well, scoring higher than 81% 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 356,609 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 17 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 70% of its contemporaries.