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Record W2138978732 · doi:10.1098/rsbl.2007.0379

Steroid hormones in bluegill, a species with male alternative reproductive tactics including female mimicry

2007· article· en· W2138978732 on OpenAlexafffund
Rosemary Knapp, Bryan D. Neff

Bibliographic record

VenueBiology Letters · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of CambridgeUniversity of OklahomaNational Science Foundation
KeywordsBiologyMatingMimicryTestosterone (patch)ZoologyEcologyMate choiceHormoneReproductive successEndocrinologyDemographyPopulation

Abstract

fetched live from OpenAlex

The proximate mechanisms underlying the evolution and maintenance of within-sex variation in mating behaviour are still poorly understood. Species characterized by alternative reproductive tactics provide ideal opportunities to investigate such mechanisms. Bluegill (Lepomis macrochirus) are noteworthy in this regard because they exhibit two distinct cuckolder (parasitic) morphs (called sneaker and satellite) in addition to the parental males that court females. Here we confirm previous findings that spawning cuckolder and parental males have significantly different levels of testosterone and 11-ketotestosterone. We also report, for the first time, that oestradiol and cortisol levels are higher in cuckolders than in parental males. The two cuckolder morphs did not differ in average levels of any of the four hormones. However, among satellite males which mimic females in appearance and behaviour, there was a strong negative relationship between oestradiol levels and body length, a surrogate for age. This finding suggests that for satellite males, oestradiol dependency of mating behaviour decreases with increasing mating experience. Although such decreased hormone dependence of mating behaviour has been reported in other taxa, our data represent the first suggestion of the relationship in fishes.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.637
Threshold uncertainty score0.243

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.048
GPT teacher head0.262
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 teacher head, 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

Citations46
Published2007
Admission routes2
Has abstractyes

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