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Record W2087568329 · doi:10.1139/b10-006

Conservation genetics of Pitcher’s thistle (<i>Cirsium pitcheri</i>), an endangered Great Lakes endemic

2010· article· en· W2087568329 on OpenAlexafffundvenueabout
Martha Gauthier, Emily Crowe, Lindsey G. Hawke, R. J. Neil Emery, Paul J. Wilson, Joanna R. Freeland

Bibliographic record

VenueBotany · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsTrent University
FundersNatural Sciences and Engineering Research Council of CanadaParks Canada
KeywordsBiologyInbreedingGenetic diversityEndangered speciesThistleBiological dispersalPopulationThreatened speciesEcologyEffective population sizeConservation geneticsSeed dispersalPopulation geneticsEvolutionary biologyZoologyMicrosatelliteDemographyGeneticsAlleleHabitat

Abstract

fetched live from OpenAlex

Pitcher's thistle ( Cirsium pitcheri Torr. ex Eaton (Torr. &amp; Gray)) is a Great Lakes endemic that in Canada is designated as threatened at both the provincial (Ontario) and national levels. Management plans will benefit from conservation genetic data, which can provide insight into population genetic diversity and differentiation. We obtained genetic data from nuclear and chloroplast microsatellite markers from 17 populations of C. pitcheri around the Great Lakes. The nuclear data revealed overall low levels of diversity, high levels of inbreeding, and low levels of population connectivity. The chloroplast data identified a single haplotype, which is consistent with reduced genetic diversity following postglacial colonization. The high levels of inbreeding within populations will likely pose a serious threat to populations in the short term; these have resulted from a combination of low connectivity between populations, and small and fluctuating population sizes. Future management of C. pitcheri populations should consider human-mediated dispersal of plants or seeds among sites.

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 score0.455
Threshold uncertainty score0.541

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 head0.017
GPT teacher head0.244
Teacher spread0.226 · 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

Citations15
Published2010
Admission routes4
Has abstractyes

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