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Reproductive roles predict sexual dimorphism in internal and external morphology of lake whitefish, <i>Coregonus clupeaformis</i>

2004· article· en· W2115369277 on OpenAlexafffund
S. J. Casselman, Albrecht I. Schulte‐Hostedde

Bibliographic record

VenueEcology Of Freshwater Fish · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsLaurentian UniversityQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSexual dimorphismBiologyCoregonus clupeaformisVitellogenesisMatingZoologyMorphology (biology)Sexual selectionMating systemThamnophis sirtalisEcologyAnatomyFish <Actinopterygii>Fishery

Abstract

fetched live from OpenAlex

Abstract – The different reproductive roles of the sexes can predict the direction and magnitude of sexual dimorphism of external and internal morphology. Males should have enlarged structures that enhance the acquisition of mating opportunities, whereas females are predicted to have enlarged organs that are associated with the production of eggs. We tested these predictions in male and female lake whitefish, a species in which both sexes have similar overall body size and shape. After controlling for body size, male lake whitefish had significantly longer jaws and pectoral and pelvic fins, larger hearts, and more muscle than females. Sexual dimorphism in relative muscle mass may be one of the most fundamental morphological differences between males and females. Females had relatively heavier livers than males. Because the liver is important for the breakdown of fats and vitellogenesis, selection should favour an enlarged liver in females for the processing of energy and the production of large numbers of eggs.

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)0.000
metaresearch head score (Gemma)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.006
GPT teacher head0.196
Teacher spread0.190 · 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

Citations54
Published2004
Admission routes2
Has abstractyes

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