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Record W2058185340 · doi:10.3390/plants2020203

Microsatellite Markers of Willow Species and Characterization of 11 Polymorphic Microsatellites for Salix eriocephala (Salicaceae), a Potential Native Species for Biomass Production in Canada

2013· article· en· W2058185340 on OpenAlexaffabout
Aurélien Lauron‐Moreau, Frédéric E. Pitre, Luc Brouillet, Michel Labrecque

Bibliographic record

VenuePlants · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBioenergy crop production and management
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsWillowSalicaceaeMicrosatelliteBiologyShrubBiomass (ecology)PopulationBotanyWoody plantGenetic markerGenetic structureAlleleGenetic variationEcologyGeneticsGene

Abstract

fetched live from OpenAlex

Biomass produced from dedicated plantations constitutes a source of renewable energy and is expected to play an important role in several countries in the coming decades. The cultivation of woody crops such as willows therefore raises several environmental issues. In North America, several native willows are potentially interesting for biomass producers. Willow trees are diverse but few species used for environmental applications have been the object of molecular genetic studies. Based on the sequenced poplar genome, 24 microsatellite markers were assayed on five native North American willow species: Salix amygdaloides, S. discolor, S. eriocephala, S. interior and S. nigra. Polymorphic microsatellite markers were used to characterize the allele data on the shrub Salix eriocephala, a North American species with economic potential. Eleven markers amplified and confirmed the potential of this species. Analysis of samples from six populations in eastern Canada showed that all markers were variable as well as polymorphic in at least one population. The number of alleles per locus ranged from 1 to 9 (mean 2.95) and showed that these microsatellite markers can be used to assess genetic diversity of North American willow 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 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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.505
Threshold uncertainty score0.899

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)0.0000.000

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 head0.012
GPT teacher head0.178
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 designBench or experimental
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

Citations9
Published2013
Admission routes2
Has abstractyes

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