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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A pitfall for machine learning methods aiming to predict across cell types
|
|---|---|
| Published in |
Genome Biology, November 2020
|
| DOI | 10.1186/s13059-020-02177-y |
| Pubmed ID | |
| Authors |
Jacob Schreiber, Ritambhara Singh, Jeffrey Bilmes, William Stafford Noble |
X Demographics
The data shown below were collected from the profiles of 96 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 | 35 | 36% |
| United Kingdom | 7 | 7% |
| Canada | 6 | 6% |
| Australia | 4 | 4% |
| Japan | 2 | 2% |
| Germany | 1 | 1% |
| China | 1 | 1% |
| Spain | 1 | 1% |
| Austria | 1 | 1% |
| Other | 5 | 5% |
| Unknown | 33 | 34% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 54 | 56% |
| Members of the public | 38 | 40% |
| Science communicators (journalists, bloggers, editors) | 2 | 2% |
| Practitioners (doctors, other healthcare professionals) | 2 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 125 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 125 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 27 | 22% |
| Researcher | 21 | 17% |
| Student > Master | 14 | 11% |
| Student > Bachelor | 10 | 8% |
| Professor > Associate Professor | 9 | 7% |
| Other | 14 | 11% |
| Unknown | 30 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 43 | 34% |
| Agricultural and Biological Sciences | 18 | 14% |
| Computer Science | 18 | 14% |
| Physics and Astronomy | 3 | 2% |
| Medicine and Dentistry | 3 | 2% |
| Other | 5 | 4% |
| Unknown | 35 | 28% |
Attention Score in Context
This research output has an Altmetric Attention Score of 50. 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 14 August 2023.
All research outputs
#856,811
of 25,692,343 outputs
Outputs from Genome Biology
#570
of 4,504 outputs
Outputs of similar age
#23,503
of 524,621 outputs
Outputs of similar age from Genome Biology
#13
of 48 outputs
Altmetric has tracked 25,692,343 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 4,504 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one has done well, scoring higher than 87% 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 524,621 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 48 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 72% of its contemporaries.