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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Dimensional analysis yields the general second-order differential equation underlying many natural phenomena: the mathematical properties of a phenomenon’s data plot then specify a unique differential equation for it
|
|---|---|
| Published in |
Theoretical Biology and Medical Modelling, August 2014
|
| DOI | 10.1186/1742-4682-11-38 |
| Pubmed ID | |
| Authors |
Gordon R Kepner |
| Abstract |
This study uses dimensional analysis to derive the general second-order differential equation that underlies numerous physical and natural phenomena described by common mathematical functions. It eschews assumptions about empirical constants and mechanisms. It relies only on the data plot's mathematical properties to provide the conditions and constraints needed to specify a second-order differential equation that is free of empirical constants for each phenomenon. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 7 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Professor | 2 | 29% |
| Other | 2 | 29% |
| Student > Bachelor | 1 | 14% |
| Student > Ph. D. Student | 1 | 14% |
| Unknown | 1 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 2 | 29% |
| Nursing and Health Professions | 2 | 29% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 14% |
| Unknown | 2 | 29% |
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 21 October 2014.
All research outputs
#18,381,794
of 22,768,097 outputs
Outputs from Theoretical Biology and Medical Modelling
#215
of 287 outputs
Outputs of similar age
#168,405
of 236,473 outputs
Outputs of similar age from Theoretical Biology and Medical Modelling
#5
of 11 outputs
Altmetric has tracked 22,768,097 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 287 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.4. This one is in the 14th percentile – i.e., 14% 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 236,473 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.