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Record W2512552209 · doi:10.1038/ncomms12452

Ovarian fluid allows directional cryptic female choice despite external fertilization

2016· article· en· W2512552209 on OpenAlexaff
Suzanne H. Alonzo, Kelly A. Stiver, Susan E. Marsh‐Rollo

Bibliographic record

VenueNature Communications · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsMcMaster University
FundersUniversity of ArizonaYale UniversityNational Science Foundation
KeywordsSpermHuman fertilizationBiologyMatingSperm competitionFemale sperm storageAndrologyFertilisationMate choiceSexual selectionIn vitro fertilisationZoologyEmbryoAnatomyGeneticsEmbryogenesisReproductive technologyMedicine

Abstract

fetched live from OpenAlex

In species with internal fertilization, females can favour certain males over others, not only before mating but also within the female's reproductive tract after mating. Here, we ask whether such directional post-mating (that is, cryptic) female mate choice can also occur in species with external fertilization. Using an in vitro sperm competition experiment, we demonstrate that female ovarian fluid (ovarian fluid) changes the outcome of sperm competition by decreasing the importance of sperm number thereby increasing the relative importance of sperm velocity. We further show that ovarian fluid does not differentially affect sperm from alternative male phenotypes, but generally enhances sperm velocity, motility, straightness and chemoattraction. Under natural conditions, female ovarian fluid likely increases the paternity of the preferred parental male phenotype, as these males release fewer but faster sperm. These results imply females have greater control over fertilization and potential to exert selection on males in species with external fertilization than previously thought possible.

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)0.001
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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.037
GPT teacher head0.285
Teacher spread0.249 · 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

Citations102
Published2016
Admission routes1
Has abstractyes

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Same venueNature CommunicationsSame topicAnimal Behavior and ReproductionFrench-language works237,207