The data shown below were collected from the profiles of 93 X users who shared this research output. Click here to find out more about how the information was compiled.
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| Title |
Machine Learning of Toxicological Big Data Enables Read-Across Structure Activity Relationships (RASAR) Outperforming Animal Test Reproducibility
|
|---|---|
| Published in |
Toxicological Sciences, July 2018
|
| DOI | 10.1093/toxsci/kfy152 |
| Pubmed ID | |
| Authors |
Thomas Luechtefeld, Dan Marsh, Craig Rowlands, Thomas Hartung |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 8 | 9% |
| Japan | 4 | 4% |
| United Kingdom | 2 | 2% |
| Spain | 2 | 2% |
| Austria | 2 | 2% |
| Switzerland | 2 | 2% |
| Australia | 2 | 2% |
| Germany | 1 | 1% |
| France | 1 | 1% |
| Other | 2 | 2% |
| Unknown | 67 | 72% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 77 | 83% |
| Scientists | 12 | 13% |
| 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 393 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 393 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 97 | 25% |
| Student > Ph. D. Student | 50 | 13% |
| Student > Master | 32 | 8% |
| Student > Bachelor | 29 | 7% |
| Other | 28 | 7% |
| Other | 57 | 15% |
| Unknown | 100 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 48 | 12% |
| Chemistry | 46 | 12% |
| Pharmacology, Toxicology and Pharmaceutical Science | 43 | 11% |
| Agricultural and Biological Sciences | 35 | 9% |
| Computer Science | 21 | 5% |
| Other | 72 | 18% |
| Unknown | 128 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 318. 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 03 September 2024.
All research outputs
#113,730
of 26,597,648 outputs
Outputs from Toxicological Sciences
#8
of 5,709 outputs
Outputs of similar age
#2,262
of 343,059 outputs
Outputs of similar age from Toxicological Sciences
#1
of 78 outputs
Altmetric has tracked 26,597,648 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,709 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one has done particularly well, scoring higher than 99% 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 343,059 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 99% of its contemporaries.
We're also able to compare this research output to 78 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.