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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Generative AI entails a credit–blame asymmetry
|
|---|---|
| Published in |
Nature Machine Intelligence, May 2023
|
| DOI | 10.1038/s42256-023-00653-1 |
| Authors |
Sebastian Porsdam Mann, Brian D. Earp, Sven Nyholm, John Danaher, Nikolaj Møller, Hilary Bowman-Smart, Joshua Hatherley, Julian Koplin, Monika Plozza, Daniel Rodger, Peter V. Treit, Gregory Renard, John McMillan, Julian Savulescu |
X Demographics
The data shown below were collected from the profiles of 59 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 | 7 | 12% |
| United Kingdom | 6 | 10% |
| Germany | 5 | 8% |
| Australia | 4 | 7% |
| Switzerland | 3 | 5% |
| Ireland | 2 | 3% |
| Singapore | 2 | 3% |
| Turkey | 2 | 3% |
| Poland | 1 | 2% |
| Other | 6 | 10% |
| Unknown | 21 | 36% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 37 | 63% |
| Scientists | 18 | 31% |
| Science communicators (journalists, bloggers, editors) | 3 | 5% |
| Practitioners (doctors, other healthcare professionals) | 1 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 30 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 17% |
| Lecturer | 2 | 7% |
| Researcher | 2 | 7% |
| Lecturer > Senior Lecturer | 1 | 3% |
| Professor > Associate Professor | 1 | 3% |
| Other | 0 | 0% |
| Unknown | 19 | 63% |
| Readers by discipline | Count | As % |
|---|---|---|
| Business, Management and Accounting | 3 | 10% |
| Philosophy | 2 | 7% |
| Computer Science | 2 | 7% |
| Engineering | 1 | 3% |
| Design | 1 | 3% |
| Other | 0 | 0% |
| Unknown | 21 | 70% |
Attention Score in Context
This research output has an Altmetric Attention Score of 99. 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 November 2023.
All research outputs
#437,611
of 25,878,862 outputs
Outputs from Nature Machine Intelligence
#128
of 783 outputs
Outputs of similar age
#9,928
of 412,071 outputs
Outputs of similar age from Nature Machine Intelligence
#4
of 46 outputs
Altmetric has tracked 25,878,862 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 783 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 68.1. This one has done well, scoring higher than 83% 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 412,071 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 97% of its contemporaries.
We're also able to compare this research output to 46 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.