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Effects of Exogenous Testosterone on Parental Care Behaviours in Male Bluegill Sunfish (<i>Lepomis macrochirus</i>)

2012· article· en· W2156239777 on OpenAlexafffund
Chandra M.C. Rodgers, Bryan D. Neff, Rosemary Knapp

Bibliographic record

VenueEthology · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Oklahoma
KeywordsPaternal careAggressionTestosterone (patch)Lepomis macrochirusTestosterone propionateZoologyPsychologyCentrarchidaeBiologyNest (protein structural motif)Fish <Actinopterygii>Developmental psychologyAndrogenEndocrinologyHormoneFisheryOffspring

Abstract

fetched live from OpenAlex

Abstract Androgens are known to mediate aggressive and defensive behaviour in many vertebrate species. However, high concentrations of androgens might also conflict with the expression of nurturing behaviours and therefore a trade‐off can exist between aggressive and nurturing behaviours during parental care. We explored the role of testosterone in paternal care in bluegill sunfish ( Lepomis macrochirus ), where males provide both sole defence of the young from predators and sole nurturing behaviour such as fanning of the eggs. At the onset of parental care, we manipulated testosterone levels in males using testosterone propionate implants. We then observed the frequency of nurturing and aggressive behaviours displayed by the males over 6 d of parental care. Testosterone‐implanted fish were more aggressive when presented with a brood predator, performing more bites, opercular flares and lateral displays than control males. Testosterone‐implanted males, however, were not less nurturing than control fish, performing similar levels of fanning and nest‐cleaning behaviours. Thus, our results support a positive relationship between testosterone and paternal aggression but no testosterone‐mediated trade‐off between paternal nurturing and aggression.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.386
Threshold uncertainty score0.208

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 head0.016
GPT teacher head0.245
Teacher spread0.228 · 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

Citations14
Published2012
Admission routes2
Has abstractyes

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