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Record W4410756048 · doi:10.1111/afe.12692

Determinants of mating success in a lek‐mating species

2025· article· en· W4410756048 on OpenAlexafffund
Joséphine Queffelec, Jeremy D. Allison, Bernard Slippers, Jaco M. Greeff

Bibliographic record

VenueAgricultural and Forest Entomology · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsNatural Resources CanadaCanadian Forest Service
FundersU.S. Forest ServiceDepartment of Forestry, Fisheries and the EnvironmentNatural Resources CanadaU.S. Department of Agriculture
KeywordsBiologyMatingMating systemEcologyEvolutionary biologyLek matingZoologyMate choice

Abstract

fetched live from OpenAlex

Abstract Leks are male‐biased aggregations formed for mating, where sperm is the only resource acquired by visiting females. One of the many advantages of leks is the possibility to efficiently assess the quality of potential mates by comparing aggregated individuals of the same sex with one another. When direct mate choice occurs in a lekking species, it is often exhibited by females, but some studies have also demonstrated the presence of male mate choice. We investigate mate choice in the lek‐forming European woodwasp, Sirex noctilio . We determine the importance of age and size as predictors of mating success. We demonstrate that mating is not random and that male and female traits affect mating success. Age plays an important role in mating success in both males and females, with older males mating more and younger females being more attractive and more receptive to mating. Relative male size seems to play a role in mating success, with males being more successful when attempting to mate with females that are larger than they are.

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 score0.058
Threshold uncertainty score0.989

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 head0.026
GPT teacher head0.231
Teacher spread0.205 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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