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Record W2107303059 · doi:10.1098/rsbl.2013.0551

Shallow gene pools in the high intertidal: extreme loss of genetic diversity in viviparous sea stars ( <i>Parvulastra</i> )

2013· article· en· W2107303059 on OpenAlexaff
Carson C. Keever, Jonathan B. Puritz, Jason A. Addison, Maria Byrne, Richard K. Grosberg, Robert J. Toonen, Michael W. Hart

Bibliographic record

VenueBiology Letters · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsKwantlen Polytechnic UniversityUniversity of New BrunswickSimon Fraser UniversityHéma-Québec
FundersAustralian Research CouncilNational Science Foundation
KeywordsBiologyBiological dispersalPopulationGenetic diversityEcologyEffective population sizeInbreedingGene flowEvolutionary biologyZoologyGenetic variationGeneticsGene

Abstract

fetched live from OpenAlex

We document an extreme example of reproductive trait evolution that affects population genetic structure in sister species of Parvulastra cushion stars from Australia. Self-fertilization by hermaphroditic adults and brood protection of benthic larvae causes strong inbreeding and range-wide genetic poverty. Most samples were fixed for a single allele at nearly all nuclear loci; heterozygotes were extremely rare (0.18%); mitochondrial DNA sequences were more variable, but few populations shared haplotypes in common. Isolation-with-migration models suggest that these patterns are caused by population bottlenecks (relative to ancestral population size) and low gene flow. Loss of genetic diversity and low potential for dispersal between high-intertidal habitats may have dire consequences for extinction risk and potential for future adaptive evolution in response to climate and other selective agents.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.958

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)0.0010.000

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 head0.020
GPT teacher head0.187
Teacher spread0.166 · 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.

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

Citations15
Published2013
Admission routes1
Has abstractyes

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