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Record W2289889614 · doi:10.1139/cjb-2015-0195

Genetic variation in <i>Silene acaulis</i> increases with population age

2016· article· en· W2289889614 on OpenAlexvenueno aff
Michaela Powolny, Peter Poschlod, Christoph Reisch

Bibliographic record

VenueBotany · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyChronosequenceGenetic variationEcologyGenetic diversityGenetic variabilitySilenePopulationEcological successionDemographyGeneticsGenotype

Abstract

fetched live from OpenAlex

This study examined the relationship between genetic variation and the mean age of individuals within populations of the alpine cushion plant Silene acaulis (L.) Jacq. along a chronosequence on a glacier foreland in the Central European Alps. We studied 67 individuals of S. acaulis from four populations located at 2390, 2530, 2680, and 2820 m a.s.l. on the glacier foreland and applied a combined approach of growth-ring analysis and individual size measurements to determine the mean age of individuals within populations. Genetic variation was studied using amplified fragment length polymorphism analysis. The mean age of individuals within populations ranged from 11 to 20 years and increased with decreasing altitude toward the older stages of the chronosequence, reaching a maximum age of 50 years. According to regression analysis, genetic variation increased slightly from early to late successional stages and was associated with the mean age of individuals within populations. The results suggest that genetic variation in S. acaulis depends on the mean age of individuals within populations, and emphasize that both species diversity and genetic diversity in plant species can increase during succession on glacier forelands. Integration of age determination methods proves to be a promising approach in the analysis of genetic variation in plant species.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.007
GPT teacher head0.205
Teacher spread0.198 · 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

Citations7
Published2016
Admission routes1
Has abstractyes

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