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Record W2133235533 · doi:10.1139/z03-078

Misinterpretation of character scaling: a tale of sexual dimorphism in body shape of common lizards

2003· article· en· W2133235533 on OpenAlexvenueno aff
Lukáš Kratochvíl, Michael Fokt, Ivan Rehák, Daniel Frynta

Bibliographic record

VenueCanadian Journal of Zoology · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicAmphibian and Reptile Biology
Canadian institutionsnot available
Fundersnot available
KeywordsSexual dimorphismBiologySnoutTraitLizardZoologyTrunkEvolutionary biologyEcologyAnatomy

Abstract

fetched live from OpenAlex

Male-biased sexual dimorphism in head, limbs, and tail scaled to snout–vent length has been reported in many lizard species. Consequently, various hypotheses have been proposed to explain observed body-shape dimorphism. According to the majority of them, the proportions of body components are adaptively related to sexual differences in ecology as well as in reproductive behaviour. Our study shows an alternative, much more parsimonious explanation in the common lizard (Lacerta vivipara). According to our analyses, the exaggeration of a single trait, specifically trunk length in females, may explain the whole pattern of sexual differences in body shape. The only consistent adaptive hypothesis, then, is that females with a larger abdominal cavity, and consequently a longer trunk, have a reproductive advantage. Size-adjusted heads, limbs, and tails traditionally reported to be larger in males than in females, features ascribed to numerous evolutionary mechanisms, thus appear to be just an artifact of inappropriate scaling to a sexually dimorphic trait (snout–vent length). As scaling to a single trait has been routinely used in many studies carried out in animals, we warn against quick interpretations based on such analyses and recommend more cautious inspection of allometries.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.049
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.049
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.007
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.224
Teacher spread0.214 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations104
Published2003
Admission routes1
Has abstractyes

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