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Record W2052904983 · doi:10.1139/z2012-031

Effects of male ejaculate on female reproductive output and longevity in <i>Photinus</i> fireflies

2012· article· en· W2052904983 on OpenAlexvenueno aff
Adam South, Sara M. Lewis

Bibliographic record

VenueCanadian Journal of Zoology · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsnot available
FundersNational Science Foundation
KeywordsSpermatophoreBiologyFecundityLongevityMatingLampyridaeZoologyReproductive successSpermOffspringMate choiceSexual conflictEcologyPopulationDemographyFirefly protocolPregnancy

Abstract

fetched live from OpenAlex

In many insects, nuptial gifts in the form of spermatophores have been shown to increase female fecundity and to contribute to female somatic maintenance. Examining how variation in male spermatophore size affects female fitness components can provide insight into the evolution of nuptial gifts, as well as insight into potential conflicts between the sexes. Here we present an experimental study on the firefly Photinus obscurellus LeConte, 1851 in which we altered spermatophore size by manipulating male mating history and examined effects on female offspring production and longevity. Females were randomly allocated to one of two mating treatments in which they mated once with a male producing either a large or a small spermatophore. We found that male spermatophore size had no significant effect on lifetime fecundity or daily reproductive rates of female P. obscurellus, but females that received a larger spermatophore showed a tendency toward longer postmating life spans. These results suggest a direct benefit to females from nuptial gifts and also reveal the potential for synergistic effects on multiple facets of female fitness.

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 score0.004

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 head0.021
GPT teacher head0.218
Teacher spread0.198 · 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

Citations16
Published2012
Admission routes1
Has abstractyes

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