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Do rational numbers play a role in selection for stochasticity?

Overview of attention for article published in Frontiers in Computational Neuroscience, September 2014
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#26 of 1,339)
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

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5 news outlets
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2 blogs
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9 Mendeley
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Title
Do rational numbers play a role in selection for stochasticity?
Published in
Frontiers in Computational Neuroscience, September 2014
DOI 10.3389/fncom.2014.00113
Pubmed ID
Authors

Robert Sinclair

Abstract

When a given tissue must, to be able to perform its various functions, consist of different cell types, each fairly evenly distributed and with specific probabilities, then there are at least two quite different developmental mechanisms which might achieve the desired result. Let us begin with the case of two cell types, and first imagine that the proportion of numbers of cells of these types should be 1:3. Clearly, a regular structure composed of repeating units of four cells, three of which are of the dominant type, will easily satisfy the requirements, and a deterministic mechanism may lend itself to the task. What if, however, the proportion should be 10:33? The same simple, deterministic approach would now require a structure of repeating units of 43 cells, and this certainly seems to require a far more complex and potentially prohibitive deterministic developmental program. Stochastic development, replacing regular units with random distributions of given densities, might not be evolutionarily competitive in comparison with the deterministic program when the proportions should be 1:3, but it has the property that, whatever developmental mechanism underlies it, its complexity does not need to depend very much upon target cell densities at all. We are immediately led to speculate that proportions which correspond to fractions with large denominators (such as the 33 of 10/33) may be more easily achieved by stochastic developmental programs than by deterministic ones, and this is the core of our thesis: that stochastic development may tend to occur more often in cases involving rational numbers with large denominators. To be imprecise: that simple rationality and determinism belong together, as do irrationality and randomness.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 11%
Unknown 8 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 44%
Student > Bachelor 3 33%
Other 1 11%
Student > Master 1 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 4 44%
Neuroscience 2 22%
Physics and Astronomy 1 11%
Biochemistry, Genetics and Molecular Biology 1 11%
Unknown 1 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 52. 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 12 November 2014.
All research outputs
#685,551
of 22,766,595 outputs
Outputs from Frontiers in Computational Neuroscience
#26
of 1,339 outputs
Outputs of similar age
#7,868
of 252,137 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#2
of 33 outputs
Altmetric has tracked 22,766,595 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,339 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.2. This one has done particularly well, scoring higher than 98% 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 252,137 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 96% of its contemporaries.
We're also able to compare this research output to 33 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.