Evidence map›Paper›PMID 31934498›Full record

ArticlePeerJ2020

Assessment of a Takagi-Sugeno-Kang fuzzy model assembly for examination of polyphasic loglinear allometry.

Hector A Echavarria-Heras, Juan R Castro-Rodriguez, Cecilia Leal-Ramirez, Enrique Villa-Diharce

Open access · goldAbstract read
In one paragraph

Article in PeerJ, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 47% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 8 citations in OpenAlex.

  1. The "fire of life cycles": age-specific metabolic scaling within and among species.Journal of comparative physiology. B, Biochemical, systemic, and environmental physiology · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 3 institutions in 1 country.

Hector A Echavarria-HerasDepartamento de Ecología, Centro de Investigación Científica y de Estudios Superiores de Ensenada, Ensenada, Baja California, México.
Juan R Castro-RodriguezFacultad de Ciencias Químicas e Ingeniería, Universidad Autónoma de Baja California, Tijuana, Baja California, México.
Cecilia Leal-RamirezDepartamento de Ecología, Centro de Investigación Científica y de Estudios Superiores de Ensenada, Ensenada, Baja California, México.
Enrique Villa-DiharceDepartamento de Estadística Aplicada, Centro de Investigacion en Matematicas, Guanajuato, Guanajuato, México.
Center for Scientific Research and Higher Education at Ensenada · MXMathematics Research Center · MXUniversidad Autónoma de Baja California · MX

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe traditional allometric analysis relies on log- transformation to contemplate linear regression in geometrical space then retransforming to get Huxley's model of simple allometry. Views assert this induces bias endorsing multi-parameter complex allometry forms and nonlinear regression in arithmetical scales. Defenders of traditional approach deem it necessary since generally organismal growth is essentially multiplicative. Then keeping allometry as originally envisioned by Huxley requires a paradigm of polyphasic loglinear allometry. A Takagi-Sugeno-Kang fuzzy model assembles a mixture of weighted sub models. This allows direct identification of break points for transition between phases. Then, this paradigm is seamlessly appropriate for efficient allometric examination of polyphasic loglinear allometry patterns. Here, we explore its suitability.

methodsPresent fuzzy model embraces firing strength weights from Gaussian membership functions and linear consequents. Weights are identified by subtractive clustering and consequents through recursive least squares or maximum likelihood. Intersection of firing strength factors set criterion to estimate breakpoints. A multi-parameter complex allometry model follows by adapting firing strengths by composite membership functions and linear consequents in arithmetical space.

resultsTakagi-Sugeno-Kang surrogates adapted complexity depending on analyzed data set. Retransformation results conveyed reproducibility strength of similar proxies identified in arithmetical space. Breakpoints were straightforwardly identified. Retransformed form implies complex allometry as a generalization of Huxley's power model involving covariate depending parameters. Huxley reported a breakpoint in the log-log plot of chela mass vs. body mass of fiddler crabs (

conclusionsOffered scheme bears reliable analysis of zero intercept allometries based on geometrical space protocols. Endorsed affine structure accommodates either polyphasic or simple allometry if whatever turns required. Interpretation of break points characterizing heterogeneity is intuitive. Analysis can be achieved in an interactive way. This could not have been obtained by relying on customary approaches. Besides, identification of break points in arithmetical scale is straightforward. Present Takagi-Sugeno-Kang arrangement offers a way to overcome the controversy between a school considering a log-transformation necessary and their critics claiming that consistent results can be only obtained through complex allometry models fitted by direct nonlinear regression in the original scales.

Indexed as

Polyphasic log linear allometryTakagi-sugeno-kang fuzzy model

Identifiers

PMID31934498
PMCPMC6951296
OpenAlexW2997641501

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.