| Title |
Chemometrics in analytical chemistry—part II: modeling, validation, and applications
|
|---|---|
| Published in |
Analytical & Bioanalytical Chemistry, August 2018
|
| DOI | 10.1007/s00216-018-1283-4 |
| Pubmed ID | |
| Authors |
Richard G. Brereton, Jeroen Jansen, João Lopes, Federico Marini, Alexey Pomerantsev, Oxana Rodionova, Jean Michel Roger, Beata Walczak, Romà Tauler |
| Abstract |
The contribution of chemometrics to important stages throughout the entire analytical process such as experimental design, sampling, and explorative data analysis, including data pretreatment and fusion, was described in the first part of the tutorial "Chemometrics in analytical chemistry." This is the second part of a tutorial article on chemometrics which is devoted to the supervised modeling of multivariate chemical data, i.e., to the building of calibration and discrimination models, their quantitative validation, and their successful applications in different scientific fields. This tutorial provides an overview of the popularity of chemometrics in analytical chemistry. |
X Demographics
The data shown below were collected from the profiles of 6 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 | 1 | 17% |
| Peru | 1 | 17% |
| Mexico | 1 | 17% |
| Unknown | 3 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 5 | 83% |
| Science communicators (journalists, bloggers, editors) | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 306 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 306 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 52 | 17% |
| Researcher | 43 | 14% |
| Student > Master | 34 | 11% |
| Student > Bachelor | 22 | 7% |
| Other | 17 | 6% |
| Other | 51 | 17% |
| Unknown | 87 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 95 | 31% |
| Agricultural and Biological Sciences | 27 | 9% |
| Engineering | 16 | 5% |
| Pharmacology, Toxicology and Pharmaceutical Science | 12 | 4% |
| Unspecified | 8 | 3% |
| Other | 35 | 11% |
| Unknown | 113 | 37% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 October 2018.
All research outputs
#15,148,294
of 25,728,855 outputs
Outputs from Analytical & Bioanalytical Chemistry
#4,526
of 9,730 outputs
Outputs of similar age
#176,596
of 342,934 outputs
Outputs of similar age from Analytical & Bioanalytical Chemistry
#41
of 177 outputs
Altmetric has tracked 25,728,855 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 9,730 research outputs from this source. They receive a mean Attention Score of 3.1. This one has gotten more attention than average, scoring higher than 52% 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 342,934 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 177 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.