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Record W2624202586

Preempting the pathogen: Blister rust and proactive management of high-elevation pines

2017· article· en· W2624202586 on OpenAlexaboutno aff
Sue Miller, Anna W. Schoettle, Kelly S. Burns, Richard A. Sniezko, Patty Champ

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicYeasts and Rust Fungi Studies
Canadian institutionsnot available
Fundersnot available
KeywordsResistance (ecology)National parkRust (programming language)GeographyAgroforestryDisease managementEcologyPopulationForest managementBiologyEnvironmental resource managementMedicineEnvironmental healthEnvironmental science
DOInot available

Abstract

fetched live from OpenAlex

White pine blister rust has been spreading through western forests since 1910, causing widespread mortality in a group that includes some of the oldest and highest-elevation pines in the United States. The disease has recently reached Colorado and is expected to travel through the southern Rockies. Although it cannot be contained, RMRS researchers and collaborators are developing proactive strategies that integrate conservation, ecology, and genetics to prepare ecosystems for invasion of the pathogen.Genetic resistance occurs in a small percentage of individuals in each of the five-needle pine species that are susceptible to the rust. Researchers and managers are identifying how common this resistance is in forest stands and where resistance is located on the landscape by collecting seeds and screening seedlings exposed to the rust for signs of disease development. This information is integrated with new ecological research on population dynamics, climate interactions, and conservation activities to develop management strategies, which may include planting of resistant seedlings or creating regeneration opportunities near resistant trees. Rocky Mountain National Park, which was hit by the rust in 2010, will be one of the first adopters of the proactive management strategy to protect their limber pine populations. Managers with the U.S. Forest Service, other National Parks, and Canadian land management agencies are also putting the proactive approach into practice.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.784
Threshold uncertainty score0.150

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 head0.253
Teacher spread0.238 · 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 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

Citations0
Published2017
Admission routes1
Has abstractyes

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