| Title |
Quality assessment and interference detection in targeted mass spectrometry data using machine learning
|
|---|---|
| Published in |
Clinical Proteomics, October 2018
|
| DOI | 10.1186/s12014-018-9209-x |
| Pubmed ID | |
| Authors |
Shadi Toghi Eshghi, Paul Auger, W. Rodney Mathews |
X Demographics
The data shown below were collected from the profiles of 7 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 | 3 | 43% |
| Spain | 1 | 14% |
| Unknown | 3 | 43% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 43% |
| Scientists | 2 | 29% |
| Science communicators (journalists, bloggers, editors) | 1 | 14% |
| Practitioners (doctors, other healthcare professionals) | 1 | 14% |
Mendeley readers
The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 18 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 22% |
| Professor | 3 | 17% |
| Student > Ph. D. Student | 2 | 11% |
| Student > Master | 2 | 11% |
| Lecturer > Senior Lecturer | 1 | 6% |
| Other | 2 | 11% |
| Unknown | 4 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 3 | 17% |
| Engineering | 2 | 11% |
| Chemistry | 2 | 11% |
| Computer Science | 2 | 11% |
| Unspecified | 1 | 6% |
| Other | 2 | 11% |
| Unknown | 6 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 21 February 2024.
All research outputs
#3,723,137
of 25,440,205 outputs
Outputs from Clinical Proteomics
#42
of 334 outputs
Outputs of similar age
#73,205
of 358,300 outputs
Outputs of similar age from Clinical Proteomics
#2
of 8 outputs
Altmetric has tracked 25,440,205 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 334 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.5. This one has done well, scoring higher than 86% 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 358,300 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 79% of its contemporaries.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 6 of them.