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Correction to: Enhancing SVM for survival data using local invariances and weighting

Overview of attention for article published in BMC Bioinformatics, August 2020
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Title
Correction to: Enhancing SVM for survival data using local invariances and weighting
Published in
BMC Bioinformatics, August 2020
DOI 10.1186/s12859-020-03558-7
Pubmed ID
Authors

Hector Sanz, Ferran Reverter, Clarissa Valim

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Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 27 August 2020.
All research outputs
#18,078,691
of 23,232,430 outputs
Outputs from BMC Bioinformatics
#6,015
of 7,359 outputs
Outputs of similar age
#284,781
of 399,131 outputs
Outputs of similar age from BMC Bioinformatics
#130
of 150 outputs
Altmetric has tracked 23,232,430 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,359 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 13th percentile – i.e., 13% of its peers scored the same or lower than it.
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We're also able to compare this research output to 150 others from the same source and published within six weeks on either side of this one. This one is in the 4th percentile – i.e., 4% of its contemporaries scored the same or lower than it.