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Mendeley readers
Attention Score in Context
| Title |
Rate-Independent Constructs for Chemical Computation
|
|---|---|
| Published in |
PLOS ONE, June 2011
|
| DOI | 10.1371/journal.pone.0021414 |
| Pubmed ID | |
| Authors |
Phillip Senum, Marc Riedel |
| Abstract |
This paper presents a collection of computational modules implemented with chemical reactions: an inverter, an incrementer, a decrementer, a copier, a comparator, a multiplier, an exponentiator, a raise-to-a-power operation, and a logarithm in base two. Unlike previous schemes for chemical computation, this method produces designs that are dependent only on coarse rate categories for the reactions ("fast" vs. "slow"). Given such categories, the computation is exact and independent of the specific reaction rates. The designs are validated through stochastic simulations of the chemical kinetics. |
Mendeley readers
The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 8% |
| Netherlands | 1 | 4% |
| United Kingdom | 1 | 4% |
| Unknown | 20 | 83% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Professor > Associate Professor | 5 | 21% |
| Student > Bachelor | 4 | 17% |
| Student > Master | 4 | 17% |
| Researcher | 4 | 17% |
| Student > Doctoral Student | 2 | 8% |
| Other | 4 | 17% |
| Unknown | 1 | 4% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 6 | 25% |
| Engineering | 4 | 17% |
| Chemistry | 4 | 17% |
| Computer Science | 3 | 13% |
| Environmental Science | 2 | 8% |
| Other | 3 | 13% |
| Unknown | 2 | 8% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 02 July 2014.
All research outputs
#5,633,478
of 22,758,248 outputs
Outputs from PLOS ONE
#68,466
of 194,191 outputs
Outputs of similar age
#31,247
of 115,141 outputs
Outputs of similar age from PLOS ONE
#699
of 2,073 outputs
Altmetric has tracked 22,758,248 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 194,191 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.1. This one has gotten more attention than average, scoring higher than 64% 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 115,141 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 72% of its contemporaries.
We're also able to compare this research output to 2,073 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.