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Total error vs. measurement uncertainty: revolution or evolution?

Overview of attention for article published in Clinical Chemistry and Laboratory Medicine, November 2015
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Title
Total error vs. measurement uncertainty: revolution or evolution?
Published in
Clinical Chemistry and Laboratory Medicine, November 2015
DOI 10.1515/cclm-2015-0997
Pubmed ID
Authors

Wytze P. Oosterhuis, Elvar Theodorsson

Abstract

The first strategic EFLM conference "Defining analytical performance goals, 15 years after the Stockholm Conference" was held in the autumn of 2014 in Milan. It maintained the Stockholm 1999 hierarchy of performance goals but rearranged them and established five task and finish groups to work on topics related to analytical performance goals including one on the "total error" theory. Jim Westgard recently wrote a comprehensive overview of performance goals and of the total error theory critical of the results and intentions of the Milan 2014 conference. The "total error" theory originated by Jim Westgard and co-workers has a dominating influence on the theory and practice of clinical chemistry but is not accepted in other fields of metrology. The generally accepted uncertainty theory, however, suffers from complex mathematics and conceived impracticability in clinical chemistry. The pros and cons of the total error theory need to be debated, making way for methods that can incorporate all relevant causes of uncertainty when making medical diagnoses and monitoring treatment effects. This development should preferably proceed not as a revolution but as an evolution.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 2%
Australia 1 2%
Unknown 61 97%

Demographic breakdown

Readers by professional status Count As %
Other 10 16%
Student > Master 8 13%
Researcher 7 11%
Student > Bachelor 4 6%
Student > Ph. D. Student 4 6%
Other 12 19%
Unknown 18 29%
Readers by discipline Count As %
Medicine and Dentistry 16 25%
Biochemistry, Genetics and Molecular Biology 11 17%
Agricultural and Biological Sciences 5 8%
Chemistry 2 3%
Veterinary Science and Veterinary Medicine 2 3%
Other 7 11%
Unknown 20 32%
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 06 November 2015.
All research outputs
#17,285,036
of 25,371,288 outputs
Outputs from Clinical Chemistry and Laboratory Medicine
#1,301
of 2,902 outputs
Outputs of similar age
#177,502
of 296,925 outputs
Outputs of similar age from Clinical Chemistry and Laboratory Medicine
#34
of 92 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,902 research outputs from this source. They receive a mean Attention Score of 3.8. This one is in the 45th percentile – i.e., 45% of its peers scored the same or lower than it.
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 296,925 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 92 others from the same source and published within six weeks on either side of this one. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.