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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Machine learning to help researchers evaluate biases in clinical trials: a prospective, randomized user study
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, May 2019
|
| DOI | 10.1186/s12911-019-0814-z |
| Pubmed ID | |
| Authors |
Frank Soboczenski, Thomas A. Trikalinos, Joël Kuiper, Randolph G. Bias, Byron C. Wallace, Iain J. Marshall |
X Demographics
The data shown below were collected from the profiles of 73 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 Kingdom | 23 | 32% |
| Canada | 4 | 5% |
| Spain | 3 | 4% |
| Ireland | 2 | 3% |
| Italy | 2 | 3% |
| Germany | 2 | 3% |
| India | 1 | 1% |
| Brazil | 1 | 1% |
| Taiwan | 1 | 1% |
| Other | 9 | 12% |
| Unknown | 25 | 34% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 42 | 58% |
| Scientists | 23 | 32% |
| Practitioners (doctors, other healthcare professionals) | 7 | 10% |
| Science communicators (journalists, bloggers, editors) | 1 | 1% |
Mendeley readers
The data shown below were compiled from readership statistics for 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 63 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 11 | 17% |
| Student > Ph. D. Student | 11 | 17% |
| Student > Master | 6 | 10% |
| Other | 5 | 8% |
| Librarian | 3 | 5% |
| Other | 8 | 13% |
| Unknown | 19 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 13 | 21% |
| Computer Science | 11 | 17% |
| Engineering | 3 | 5% |
| Psychology | 3 | 5% |
| Arts and Humanities | 2 | 3% |
| Other | 9 | 14% |
| Unknown | 22 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 41. 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 2020.
All research outputs
#1,022,604
of 25,711,998 outputs
Outputs from BMC Medical Informatics and Decision Making
#34
of 2,156 outputs
Outputs of similar age
#22,607
of 365,449 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#2
of 48 outputs
Altmetric has tracked 25,711,998 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,156 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done particularly well, scoring higher than 98% 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 365,449 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 93% of its contemporaries.
We're also able to compare this research output to 48 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 95% of its contemporaries.