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Record W2340470450 · doi:10.20381/ruor-2929

Assessing Territoriality as a Component of Male Sexual Fitness in 'Drosophila serrata'

2013· dissertation· en· W2340470450 on OpenAlexfundno aff
Alison White

Bibliographic record

VenueuO Research (University of Ottawa) · 2013
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Ottawa
KeywordsTerritorialityComponent (thermodynamics)BiologyEvolutionary biologyZoologyEcologyPhysics

Abstract

fetched live from OpenAlex

While the phenotypic effects of sexual selection have been well studied, the consequences for population mean fitness remain unclear. Additionally, there is a need to more fully characterize how various forms of inter- and intrasexual selection combine to affect the evolution of traits under sexual selection. Here, I address these issues as they relate to male territoriality in Drosophila serrata, a model system for the study of female preference for male pheromones. First, I demonstrate that territoriality occurs and is a likely component of male sexual fitness. Results from a phenotypic manipulation indicate that territorial success was also condition-dependent, and that sexual selection against low condition males tended to be stronger given a high opportunity for territory defense. Territorial success depended on body size but not on pheromones. How this and other components of male mating success interact to affect trait evolution and population mean fitness remains an important area for future study.

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 score0.003

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 head0.094
GPT teacher head0.339
Teacher spread0.245 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

Explore more

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