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Record W2164698469 · doi:10.1139/x07-215

Genetic structures of common ash (<i>Fraxinus excelsior</i>) populations in Germany at sites differing in water regimes

2008· article· en· W2164698469 on OpenAlexvenueno aff
Mareike Rüdinger, Judith Glaeser, Ingrid Hebel, Aikaterini Dounavi

Bibliographic record

VenueCanadian Journal of Forest Research · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsnot available
FundersForskningsrådet om Hälsa, Arbetsliv och Välfärd
KeywordsBiologyEcotypeIsozymeFraxinusGenetic diversityAlleleAlcohol dehydrogenaseLocus (genetics)Genetic variationEcologyBotanyGeneticsEnzymePopulationGeneBiochemistry

Abstract

fetched live from OpenAlex

The genetic structure of the alcohol dehydrogenase (ADH) enzyme complex was studied by means of isozyme analysis among several common ash ( Fraxinus excelsior L.) provenances. We analysed if specific alloforms of locus ADH-B are selected under flooding stress caused by oxygen deprivation, since ADH is a fundamental enzyme of the plant metabolism under anoxia. This selection, if given, could therefore result in different ash ecotypes. Furthermore, genetic structures in the same provenances resulting from the analysis of four nuclear microsatellite markers are also discussed and compared with those resulting from the isozyme analyses to differentiate between adaptation and demographical processes. We found the highest value of genetic diversity at one of the two examined floodplains but did not find significant correlations between genotypes structures and flooding. The observed allele distributions can be mainly attributed to high human pressure and important seed transport events. These are regarded as the main forces shaping the actual genotype distributions rather than selection processes acting on locus ADH-B.

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)0.000
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 score0.022
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.060
GPT teacher head0.304
Teacher spread0.244 · 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

Citations17
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Forest Research→Same topicGenetic diversity and population structure→French-language works237,207→