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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Feasibility and evaluation of a large-scale external validation approach for patient-level prediction in an international data network: validation of models predicting stroke in female patients newly diagnosed with atrial fibrillation
|
|---|---|
| Published in |
BMC Medical Research Methodology, May 2020
|
| DOI | 10.1186/s12874-020-00991-3 |
| Pubmed ID | |
| Authors |
Jenna M. Reps, Ross D. Williams, Seng Chan You, Thomas Falconer, Evan Minty, Alison Callahan, Patrick B. Ryan, Rae Woong Park, Hong-Seok Lim, Peter Rijnbeek |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Members of the public | 1 | 50% |
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 % |
|---|---|---|
| Researcher | 7 | 23% |
| Student > Doctoral Student | 3 | 10% |
| Student > Bachelor | 3 | 10% |
| Student > Ph. D. Student | 3 | 10% |
| Student > Master | 2 | 7% |
| Other | 1 | 3% |
| Unknown | 11 | 37% |
| Readers by discipline | Count | As % |
|---|---|---|
| Nursing and Health Professions | 4 | 13% |
| Computer Science | 4 | 13% |
| Medicine and Dentistry | 4 | 13% |
| Business, Management and Accounting | 1 | 3% |
| Social Sciences | 1 | 3% |
| Other | 3 | 10% |
| Unknown | 13 | 43% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 02 March 2022.
All research outputs
#6,915,012
of 25,019,109 outputs
Outputs from BMC Medical Research Methodology
#1,028
of 2,232 outputs
Outputs of similar age
#132,885
of 386,695 outputs
Outputs of similar age from BMC Medical Research Methodology
#48
of 73 outputs
Altmetric has tracked 25,019,109 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 2,232 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.4. This one has gotten more attention than average, scoring higher than 53% 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 386,695 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
We're also able to compare this research output to 73 others from the same source and published within six weeks on either side of this one. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.