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Record W2558608321 · doi:10.1139/cjb-2016-0144

Genetic structure of the American ginseng (<i>Panax quinquefolius</i> L.) in Eastern Canada using reduced-representation high-throughput sequencing

2016· article· en· W2558608321 on OpenAlexafffundvenueabout
Simon Joly, Annie Archambault, Stéphanie Pellerin, Andrée Nault

Bibliographic record

VenueBotany · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGinseng Biological Effects and Applications
Canadian institutionsMontreal BiodomeUniversité de MontréalEspace pour la vie
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyGinsengGenetic structureRange (aeronautics)Genetic variationGenetic variabilityHabitatAmerican ginsengGenetic diversityPopulationEcologyGeneGeneticsDemographyGenotype

Abstract

fetched live from OpenAlex

The American ginseng (Panax quinquefolius L.) has been used for a wide range of medicinal purposes for more than 300 years, and is at risk in most of its range because of harvesting in natural populations, herbivory, and habitat loss. Its genetic structure is largely unknown in the previously glaciated areas of Eastern Canada, although such information could provide useful information for restoration strategies. We generated and analysed data from a reduced-representation high-throughput sequencing approach with a BAMOVA population model to partition the genetic variation within and among six natural populations of American ginseng in Eastern Canada. We found that an important and significant fraction of the genetic variation was structured among populations ([Formula: see text] = 42%; F ST = 34%) at the geographical scale of the study (&lt;250 km). No clear evidence of isolation-by-distance was observed. This important genetic structure observed among American ginseng populations from a region that was covered by ice during the last glaciations is similar to what had been found in previous studies on southern populations or throughout the species range.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.345
Threshold uncertainty score0.872

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 head0.014
GPT teacher head0.254
Teacher spread0.241 · 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

Citations4
Published2016
Admission routes4
Has abstractyes

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