| Title |
Auto-generated materials database of Curie and Néel temperatures via semi-supervised relationship extraction
|
|---|---|
| Published in |
Scientific Data, June 2018
|
| DOI | 10.1038/sdata.2018.111 |
| Pubmed ID | |
| Authors |
Callum J. Court, Jacqueline M. Cole |
| Abstract |
Large auto-generated databases of magnetic materials properties have the potential for great utility in materials science research. This article presents an auto-generated database of 39,822 records containing chemical compounds and their associated Curie and Néel magnetic phase transition temperatures. The database was produced using natural language processing and semi-supervised quaternary relationship extraction, applied to a corpus of 68,078 chemistry and physics articles. Evaluation of the database shows an estimated overall precision of 73%. Therein, records processed with the text-mining toolkit, ChemDataExtractor, were assisted by a modified Snowball algorithm, whose original binary relationship extraction capabilities were extended to quaternary relationship extraction. Consequently, its machine learning component can now train with ≤ 500 seeds, rather than the 4,000 originally used. Data processed with the modified Snowball algorithm affords 82% precision. Database records are available in MongoDB, CSV and JSON formats which can easily be read using Python, R, Java and MatLab. This makes the database easy to query for tackling big-data materials science initiatives and provides a basis for magnetic materials discovery. |
X Demographics
The data shown below were collected from the profiles of 18 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 | 2 | 11% |
| South Africa | 2 | 11% |
| Guinea | 1 | 6% |
| Japan | 1 | 6% |
| Malta | 1 | 6% |
| Australia | 1 | 6% |
| United States | 1 | 6% |
| Unknown | 9 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 15 | 83% |
| Scientists | 3 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 111 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 111 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 21 | 19% |
| Researcher | 18 | 16% |
| Student > Bachelor | 12 | 11% |
| Student > Master | 11 | 10% |
| Professor | 5 | 5% |
| Other | 14 | 13% |
| Unknown | 30 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Materials Science | 21 | 19% |
| Chemistry | 13 | 12% |
| Physics and Astronomy | 10 | 9% |
| Engineering | 7 | 6% |
| Computer Science | 6 | 5% |
| Other | 19 | 17% |
| Unknown | 35 | 32% |
Attention Score in Context
This research output has an Altmetric Attention Score of 13. 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 08 February 2021.
All research outputs
#2,534,613
of 24,271,113 outputs
Outputs from Scientific Data
#956
of 2,884 outputs
Outputs of similar age
#51,787
of 332,051 outputs
Outputs of similar age from Scientific Data
#29
of 68 outputs
Altmetric has tracked 24,271,113 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,884 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 23.8. This one has gotten more attention than average, scoring higher than 66% 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 332,051 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 84% of its contemporaries.
We're also able to compare this research output to 68 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 58% of its contemporaries.