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Record W2343207176 · doi:10.1098/rsbl.2016.0105

Genetic variation in male-induced harm in <i>Drosophila melanogaster</i>

2016· article· en· W2343207176 on OpenAlexafffund
David C. S. Filice, Tristan A. F. Long

Bibliographic record

VenueBiology Letters · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsWilfrid Laurier University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyFecundityDrosophila melanogasterHarmCourtshipLongevityZoologyGenetic variationEvolutionary biologyDemographyGeneticsPopulationGene

Abstract

fetched live from OpenAlex

In Drosophila melanogaster, prolonged exposure to males reduces the longevity and fecundity of females. This harm arises from the effects of male courtship behaviours and the toxic side effects of the accessory gland proteins (Acps) in their seminal fluids. Here, we examine the relationship between male exposure and its harmful effect on the lifetime fitness of his mates, and quantify the genetic basis for this variation. We found significant additive genetic variation in the magnitude of harm that males impose on females by exposing females to males from a variety of hemiclonal backgrounds for either a brief or prolonged period of time and measuring their fecundity, a meaningful fitness index. Furthermore, we discovered a strong negative correlation between the magnitude of harm and the short-term effects of male exposure on female fitness. We discuss the evolutionary significance of these results with regards to potential life-history trade-offs in females, and its relationship to male body size.

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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.025
GPT teacher head0.231
Teacher spread0.206 · 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

Citations19
Published2016
Admission routes2
Has abstractyes

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