Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 417

The DOI matches its Crossref record.

Genetical Aspects of Metrical Growth and Form in Animals

Cock, A. G.·1966·The Quarterly Review of Biology

Abstract

The ontogenesis of those genetic differences in form which are homeomorphic, that is, which can be expressed in terms of meausrements, is considered. Particualar stress is laid on the advantages of longitudinal (versus cross-sectional, static, and mixed) data, and on the necessity of adapting the method of analysis to the type of data. Bivariate and multivariate methods of analysis are discussed, and the analysis of simple allometry is treated in detail. No existing multivariate method is competent to deal with longitudinal data; a way of overcoming this is suggested. Work on single-gene and multiple-gene diferences, and comparisons between related species, are critically examined. Instances in which the allometry line is simply shifted in position, without change in K (the coefficient of allometry) are common; well-established differences in K are relatively rare. When differences in K do occur, they often result in intersection of the allometry lines, or in convergence toward older ages. It is suggested that this results from the combined effects of genes which singly affect either position alone, or K. Evolutionary allometry is held to be a description of evolutionary trends, not an explanation of them in terms of growth. Theories of growth control and regeneration are discussed, and aspects which need reexamination using longitudinal methods of analysis are indicated.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1086/404940

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 417

Metadata

Authors
Cock, A. G.
Venue
The Quarterly Review of Biology
Published
1966-06
Volume
41
Issue
2
Pages
131-190
ISSN
  • 0033-5770 (ISSN-L)
  • 1539-7718
OpenAlex
W2040891701
Cited by
417
References
0
FWCI
2.87
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Genetical Aspects of Metrical Growth and Form in Animals. https://app.cochat.ai/papers/10.1086/404940
The paper
Cock, A. G. (1966). Genetical Aspects of Metrical Growth and Form in Animals. The Quarterly Review of Biology. https://doi.org/10.1086/404940

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.