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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A community challenge to predict clinical outcomes after immune checkpoint blockade in non-small cell lung cancer
|
|---|---|
| Published in |
Journal of Translational Medicine, February 2024
|
| DOI | 10.1186/s12967-023-04705-3 |
| Pubmed ID | |
| Authors |
Mike Mason, Óscar Lapuente-Santana, Anni S. Halkola, Wenyu Wang, Raghvendra Mall, Xu Xiao, Jacob Kaufman, Jingxin Fu, Jacob Pfeil, Jineta Banerjee, Verena Chung, Han Chang, Scott D. Chasalow, Hung Ying Lin, Rongrong Chai, Thomas Yu, Francesca Finotello, Tuomas Mirtti, Mikko I. Mäyränpää, Jie Bao, Emmy W. Verschuren, Eiman I. Ahmed, Michele Ceccarelli, Lance D. Miller, Gianni Monaco, Wouter R. L. Hendrickx, Shimaa Sherif, Lin Yang, Ming Tang, Shengqing Stan Gu, Wubing Zhang, Yi Zhang, Zexian Zeng, Avinash Das Sahu, Yang Liu, Wenxian Yang, Davide Bedognetti, Jing Tang, Federica Eduati, Teemu D. Laajala, William J. Geese, Justin Guinney, Joseph D. Szustakowski, Benjamin G. Vincent, David P. Carbone |
X Demographics
The data shown below were collected from the profiles of 20 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Finland | 4 | 20% |
| United States | 4 | 20% |
| Spain | 1 | 5% |
| Germany | 1 | 5% |
| Italy | 1 | 5% |
| Austria | 1 | 5% |
| Unknown | 8 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 11 | 55% |
| Members of the public | 7 | 35% |
| Practitioners (doctors, other healthcare professionals) | 2 | 10% |
Mendeley readers
The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 13 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 31% |
| Other | 2 | 15% |
| Student > Master | 2 | 15% |
| Professor | 1 | 8% |
| Student > Postgraduate | 1 | 8% |
| Other | 0 | 0% |
| Unknown | 3 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 4 | 31% |
| Engineering | 2 | 15% |
| Nursing and Health Professions | 1 | 8% |
| Veterinary Science and Veterinary Medicine | 1 | 8% |
| Medicine and Dentistry | 1 | 8% |
| Other | 1 | 8% |
| Unknown | 3 | 23% |
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 01 March 2024.
All research outputs
#2,744,017
of 25,394,081 outputs
Outputs from Journal of Translational Medicine
#480
of 4,639 outputs
Outputs of similar age
#19,928
of 180,495 outputs
Outputs of similar age from Journal of Translational Medicine
#8
of 62 outputs
Altmetric has tracked 25,394,081 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 4,639 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one has done well, scoring higher than 89% 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 180,495 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 89% of its contemporaries.
We're also able to compare this research output to 62 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.