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Record W4403893398 · doi:10.1098/rsos.231198

Are testosterone pulses a physiological mechanism for expanding activity beyond territories?

2024· article· en· W4403893398 on OpenAlexaff
Radmila Petric, Matina C. Kalcounis‐Rueppell, Catherine A. Marler

Bibliographic record

VenueRoyal Society Open Science · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversity of Alberta
FundersUniversity of North Carolina at Greensboro
KeywordsAggressionTestosterone (patch)TerritorialityPsychologyBiologyDevelopmental psychologyEndocrinologyCommunication

Abstract

fetched live from OpenAlex

We ask whether artificially induced testosterone pulses (T-pulses), administered to males in the wild at the territory boundary, adjust location preferences within the territory. Multiple transient T-pulses occurring after social interactions in males can alter behaviour and spatial preferences. We previously found that T-pulses administered at the nest induce male California mice, a biparental and territorial species, to spend more time at the nest likely through conditioned place preferences. We hypothesized that T's reinforcing effects would increase future time by the T-injected males at the boundary and promote territorial defence. Contrary to predictions, T-pulses induced a decrease in male time at the boundary, and instead appeared to promote male territorial/home range expansion, accompanied by shorter sustained vocalizations (SVs) and decreased proportion of three SV bouts. Shorter SVs are associated with aggression in the laboratory. Furthermore, in response to T-male behavioural changes, uninjected female partners decreased boundary time. Our results suggest new functions for socially induced T-pulses, such as extending territorial boundaries/home ranges. Location preferences induced through reinforcing/rewarding mechanisms may be more plastic and dependent on physical and social contexts than previously thought. Moreover, the results suggest that location preferences produced through rewarding/reinforcing mechanisms can be viewed from adaptive perspectives to influence future behaviour.

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)0.000
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.058
GPT teacher head0.323
Teacher spread0.266 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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