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A dynamic prognostic model to predict survival in post–polycythemia vera myelofibrosis

Overview of attention for article published in Blood, April 2008
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (66th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
1 tweeter
patent
2 patents

Citations

dimensions_citation
87 Dimensions

Readers on

mendeley
39 Mendeley
citeulike
1 CiteULike
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Title
A dynamic prognostic model to predict survival in post–polycythemia vera myelofibrosis
Published in
Blood, April 2008
DOI 10.1182/blood-2007-11-121434
Pubmed ID
Authors

Francesco Passamonti, Elisa Rumi, Marianna Caramella, Chiara Elena, Luca Arcaini, Emanuela Boveri, Cecilia Del Curto, Daniela Pietra, Laura Vanelli, Paolo Bernasconi, Cristiana Pascutto, Mario Cazzola, Enrica Morra, Mario Lazzarino

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Vietnam 1 3%
Unknown 37 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 21%
Student > Ph. D. Student 7 18%
Other 6 15%
Unspecified 5 13%
Student > Master 4 10%
Other 9 23%
Readers by discipline Count As %
Medicine and Dentistry 21 54%
Unspecified 6 15%
Agricultural and Biological Sciences 5 13%
Biochemistry, Genetics and Molecular Biology 2 5%
Pharmacology, Toxicology and Pharmaceutical Science 2 5%
Other 3 8%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 09 April 2018.
All research outputs
#3,264,867
of 12,781,938 outputs
Outputs from Blood
#6,109
of 16,926 outputs
Outputs of similar age
#91,326
of 274,157 outputs
Outputs of similar age from Blood
#161
of 237 outputs
Altmetric has tracked 12,781,938 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 16,926 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.1. This one has gotten more attention than average, scoring higher than 61% 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 274,157 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 237 others from the same source and published within six weeks on either side of this one. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.