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Record W2145692625 · doi:10.1163/1568539x-00003261

Nonapeptide influences on social behaviour: effects of vasotocin and isotocin on shoaling and interaction in zebrafish

2015· article· en· W2145692625 on OpenAlexaff
Charlotte M. Lindeyer, Esther M. A. Langen, William T. Swaney, Simon M. Reader

Bibliographic record

VenueBehaviour · 2015
Typearticle
Languageen
FieldPsychology
TopicNeuroendocrine regulation and behavior
Canadian institutionsMcGill University
FundersUniversitair Medisch Centrum UtrechtUniversiteit Utrecht
KeywordsVasotocinShoaling and schoolingShoalBiologyVertebrateZoologyEcologyNeuropeptideGeology

Abstract

fetched live from OpenAlex

Nonapeptides are important regulators of social behaviour across vertebrate taxa. While their role in simple grouping behaviour has been explored in estrildid finches, other taxa are understudied, prompting us to investigate nonapeptide influences on shoaling behaviour in zebrafish. Subjects received injections of isotocin, an isotocin antagonist, vasotocin, a vasotocin antagonist, or saline, followed by a test of grouping behaviour. Vasotocin decreased social interaction with the shoal. Unexpectedly, the vasotocin antagonist also reduced social interaction with the shoal, as well as general shoaling behaviour. Isotocin and its antagonist had minimal effects on grouping behaviours. These results suggest social interaction and shoaling are discrete aspects of sociality differentially influenced by vasotocin, although we cannot discount possible anxiogenic effects of vasotocin. Contrasting these results with studies in other systems demonstrates that each nonapeptide’s role in social behaviour varies across taxa, and cautions against a simplistic characterisation of nonapeptides as prosocial regulators of 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

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 integrity0.0000.001
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 head0.057
GPT teacher head0.376
Teacher spread0.319 · 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 designBench or experimental
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

Citations37
Published2015
Admission routes1
Has abstractyes

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