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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Beyond the hype: deep neural networks outperform established methods using a ChEMBL bioactivity benchmark set
|
|---|---|
| Published in |
Journal of Cheminformatics, August 2017
|
| DOI | 10.1186/s13321-017-0232-0 |
| Pubmed ID | |
| Authors |
Eelke B. Lenselink, Niels ten Dijke, Brandon Bongers, George Papadatos, Herman W. T. van Vlijmen, Wojtek Kowalczyk, Adriaan P. IJzerman, Gerard J. P. van Westen |
X Demographics
The data shown below were collected from the profiles of 31 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 | 8 | 26% |
| Spain | 3 | 10% |
| Netherlands | 3 | 10% |
| Comoros | 1 | 3% |
| Saudi Arabia | 1 | 3% |
| Thailand | 1 | 3% |
| United Kingdom | 1 | 3% |
| Russia | 1 | 3% |
| Israel | 1 | 3% |
| Other | 4 | 13% |
| Unknown | 7 | 23% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 16 | 52% |
| Scientists | 14 | 45% |
| Science communicators (journalists, bloggers, editors) | 1 | 3% |
Mendeley readers
The data shown below were compiled from readership statistics for 407 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 407 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 82 | 20% |
| Student > Ph. D. Student | 73 | 18% |
| Student > Master | 50 | 12% |
| Student > Bachelor | 43 | 11% |
| Other | 19 | 5% |
| Other | 39 | 10% |
| Unknown | 101 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 76 | 19% |
| Computer Science | 50 | 12% |
| Biochemistry, Genetics and Molecular Biology | 44 | 11% |
| Pharmacology, Toxicology and Pharmaceutical Science | 43 | 11% |
| Agricultural and Biological Sciences | 24 | 6% |
| Other | 61 | 15% |
| Unknown | 109 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 32. 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 July 2023.
All research outputs
#1,259,010
of 25,837,817 outputs
Outputs from Journal of Cheminformatics
#56
of 981 outputs
Outputs of similar age
#24,744
of 330,013 outputs
Outputs of similar age from Journal of Cheminformatics
#3
of 12 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 981 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.0. This one has done particularly well, scoring higher than 94% 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 330,013 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 92% of its contemporaries.
We're also able to compare this research output to 12 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.