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Record W2987200879 · doi:10.21083/surg.v11i0.5407

Female size and pre-copulatory sexual selection by males of intertidal snail (Littorina saxatilis)

2019· article· en· W2987200879 on OpenAlexvenueno aff
Nora Alsafi

Bibliographic record

VenueSURG Journal · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicCrustacean biology and ecology
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyMatingSexual selectionFecundityMate choiceMating preferencesZoologyEcotypeEcologyDemographyPopulation

Abstract

fetched live from OpenAlex

Littorina saxatilis, the rough periwinkle, is highly promiscuous and polyandrous; female L. saxatilis snails rarely reject male advances. Sexual selection by males has been observed in this species. Sexual selection is one of the driving forces of evolution and may be a significant contributor to partial reproductive isolation between two ecotypes of L. saxatilis. Male sexual selection based on female size was investigated for wave-exposed crab ecotype snails in this study. Males and females were measured and placed in mating arenas. Males were presented with a choice of a smaller or larger female relative to themselves. Mating frequency and duration was recorded. A total of 19 successful trials were performed. A significantly higher mating frequency (p<0.005) was associated with larger females, indicating that males exhibit strong pre-copulatory sexual selection. Mating duration was significantly longer for larger female mating events (p<0.05) but was also equally determined by male size (p<0.05) as larger males tended to mate for longer. These results indicate that a strong sexual selection by males exists for L. saxatilis, in which larger females are preferred. This behavior may be a response to perceived fecundity of females, and/or may be a product of selection against hybrids.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

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)0.0060.000

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 head0.006
GPT teacher head0.220
Teacher spread0.214 · 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 teacher head, not a consensus.

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
Published2019
Admission routes1
Has abstractyes

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