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Record W2004130595 · doi:10.1094/phyto-95-0793

Molecular Epidemiology of White Pine Blister Rust: Recombination and Spatial Distribution

2005· article· en· W2004130595 on OpenAlexaff
Richard C. Hamelin, Maura Allaire, Marie‐Josée Bergeron, Marie-Claude Nicole, Nicole Lecours

Bibliographic record

VenuePhytopathology · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicYeasts and Rust Fungi Studies
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsBiologyBiological dispersalHaplotypeRecombinationStripe rustPloidySporeSpatial distributionGeneticsRust (programming language)Genetic diversityWhite (mutation)BotanyEvolutionary biologyGenotypePlant disease resistancePopulation

Abstract

fetched live from OpenAlex

ABSTRACT Multilocus haplotypes (MLHs) were derived for the spermogonial (monokaryotic haploid) stage of Cronartium ribicola, the causal agent of white pine blister rust. Six random amplified polymorphic DNA loci and three single-strand conformational polymorphism markers were analyzed for 246 rust samples collected from two heavily infected white pine plantations. All cankers sampled were spatially located within the plantations. The hypothesis that spores are not locally disseminated was supported by the absence of any spatial clustering in the distribution of the MLHs. A large number of MLHs was found at both sites and the haplotypic diversity was close to the maximum (one) in both populations. All measures of recombination were not different from expectations under a scenario of sexual recombination. Genetic differentiation between the two sites was very low (theta = 0.023), yet it was significantly different from zero (P < 0.01). This analysis is in agreement with a scenario of extensive sexual recombination followed by some long-distance dispersal.

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)0.0000.000

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 head0.264
Teacher spread0.252 · 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

Citations18
Published2005
Admission routes1
Has abstractyes

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