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Record W2030091522 · doi:10.1086/516718

Sperm Competition and the Evolution of Ejaculate Composition

2007· article· en· W2030091522 on OpenAlexaff
Erin K. Cameron, Troy Day, Locke Rowe

Bibliographic record

VenueThe American Naturalist · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of TorontoQueen's UniversityMcGill University
Fundersnot available
KeywordsSperm competitionSpermBiologySemenCompetition (biology)Composition (language)Function (biology)Female sperm storageEvolutionary biologyEcologyGenetics

Abstract

fetched live from OpenAlex

We present a model of sperm competition that incorporates both sperm and nonsperm parts of the ejaculate. Our primary focus is on determining how ejaculate composition and size evolves as a function of the effects of seminal fluid on male reproductive success and as a function of asymmetry in sperm usage by females. The model predicts that different patterns of investment in sperm and seminal products are expected to evolve as a function of the bias in sperm usage by females. It also predicts the evolution of distinct patterns in ejaculate composition depending on the function of seminal fluid. In the discussion, we highlight a number of potential approaches for testing the theory that we develop.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.013
GPT teacher head0.211
Teacher spread0.199 · 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

Citations105
Published2007
Admission routes1
Has abstractyes

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