| Title |
Different mechanisms underlie implicit visual statistical learning in honey bees and humans
|
|---|---|
| Published in |
Proceedings of the National Academy of Sciences of the United States of America, September 2020
|
| DOI | 10.1073/pnas.1919387117 |
| Pubmed ID | |
| Authors |
Aurore Avarguès-Weber, Valerie Finke, Márton Nagy, Tūnde Szabó, Daniele d'Amaro, Adrian G Dyer, József Fiser |
X Demographics
The data shown below were collected from the profiles of 39 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 5 | 13% |
| France | 3 | 8% |
| United States | 3 | 8% |
| United Kingdom | 3 | 8% |
| Italy | 2 | 5% |
| Hungary | 2 | 5% |
| Japan | 1 | 3% |
| Austria | 1 | 3% |
| Singapore | 1 | 3% |
| Other | 3 | 8% |
| Unknown | 15 | 38% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 26 | 67% |
| Scientists | 10 | 26% |
| Science communicators (journalists, bloggers, editors) | 3 | 8% |
Mendeley readers
The data shown below were compiled from readership statistics for 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 77 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 14 | 18% |
| Student > Ph. D. Student | 13 | 17% |
| Student > Bachelor | 10 | 13% |
| Student > Master | 6 | 8% |
| Student > Doctoral Student | 4 | 5% |
| Other | 8 | 10% |
| Unknown | 22 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 19 | 25% |
| Neuroscience | 11 | 14% |
| Agricultural and Biological Sciences | 9 | 12% |
| Environmental Science | 3 | 4% |
| Computer Science | 2 | 3% |
| Other | 8 | 10% |
| Unknown | 25 | 32% |
Attention Score in Context
This research output has an Altmetric Attention Score of 67. 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 24 October 2023.
All research outputs
#648,351
of 25,759,158 outputs
Outputs from Proceedings of the National Academy of Sciences of the United States of America
#10,965
of 103,679 outputs
Outputs of similar age
#18,523
of 434,494 outputs
Outputs of similar age from Proceedings of the National Academy of Sciences of the United States of America
#330
of 1,068 outputs
Altmetric has tracked 25,759,158 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 103,679 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 39.6. This one has done well, scoring higher than 89% 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 434,494 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 95% of its contemporaries.
We're also able to compare this research output to 1,068 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 69% of its contemporaries.