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Large and persistent effect of a female steroid pheromone on ejaculate size in goldfish <i>Carassius auratus</i>

2008· article· en· W2011377764 on OpenAlexaff
Drew J. Hoysak, N. E. Stacey

Bibliographic record

VenueJournal of Fish Biology · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBiologyPheromoneSpermCarassius auratusMorningHuman fertilizationMiltEndocrinologyZoologyInternal medicineAndrologyAnimal scienceEcologyAnatomyFish <Actinopterygii>FisheryBotany

Abstract

fetched live from OpenAlex

This study determined if ejaculate size in male goldfish Carassius auratus is increased by the female preovulatory steroid pheromone 4‐pregnen‐17,20β‐diol‐3‐one (17,20βP), which previously has been shown to affect male behaviour and to increase sperm motility and stripped sperm number, and also to increase paternity in competitive spawning and competitive in vitro fertilization. Experimental males were exposed overnight to 17,20βP whereas control males were not. The morning following exposure, each male was placed with a reproductively active female and, after one to 20 spawning acts, aquarium water was sampled to quantify released sperm. Although exposure to 17,20βP induced a five‐fold difference in the number of sperm that could be stripped, the median number of sperm in first ejaculates of pheromone‐exposed males was >60 sixty times that of control males, a pheromonal effect on ejaculate size that persisted for at least 20 spawning acts. The magnitude of the pheromone effect on ejaculate size indicates that it is a critical component of C. auratus sperm allocation, and that examining this effect in concert with other factors (e.g. presence of competitors, male and female size and frequency of spawning) will reveal the contribution of the preovulatory pheromone to male fitness in this promiscuous species.

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 score0.003
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)0.0010.000

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 head0.017
GPT teacher head0.236
Teacher spread0.219 · 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

Citations14
Published2008
Admission routes1
Has abstractyes

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