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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
|
|---|---|
| Published in |
Nature Machine Intelligence, May 2019
|
| DOI | 10.1038/s42256-019-0048-x |
| Pubmed ID | |
| Authors |
Cynthia Rudin |
X Demographics
The data shown below were collected from the profiles of 337 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 | 67 | 20% |
| United Kingdom | 23 | 7% |
| Germany | 11 | 3% |
| France | 10 | 3% |
| Switzerland | 9 | 3% |
| Spain | 9 | 3% |
| Netherlands | 7 | 2% |
| Australia | 5 | 1% |
| India | 5 | 1% |
| Other | 63 | 19% |
| Unknown | 128 | 38% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 196 | 58% |
| Scientists | 132 | 39% |
| Science communicators (journalists, bloggers, editors) | 5 | 1% |
| Practitioners (doctors, other healthcare professionals) | 4 | 1% |
Mendeley readers
The data shown below were compiled from readership statistics for 3,669 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 3669 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 696 | 19% |
| Student > Master | 466 | 13% |
| Researcher | 439 | 12% |
| Student > Bachelor | 243 | 7% |
| Student > Doctoral Student | 149 | 4% |
| Other | 463 | 13% |
| Unknown | 1213 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 881 | 24% |
| Engineering | 360 | 10% |
| Medicine and Dentistry | 106 | 3% |
| Social Sciences | 93 | 3% |
| Business, Management and Accounting | 88 | 2% |
| Other | 745 | 20% |
| Unknown | 1396 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 501. 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 March 2024.
All research outputs
#52,452
of 25,837,817 outputs
Outputs from Nature Machine Intelligence
#16
of 774 outputs
Outputs of similar age
#1,013
of 368,318 outputs
Outputs of similar age from Nature Machine Intelligence
#1
of 27 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 774 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 68.8. This one has done particularly well, scoring higher than 97% 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 368,318 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 99% of its contemporaries.
We're also able to compare this research output to 27 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 96% of its contemporaries.