MétaCan
Menu
Back to cohort
Record W2144883038 · doi:10.1139/x06-231

The distribution and incidence of white pine blister rust in central and southeastern Wyoming and northern Colorado

2007· article· en· W2144883038 on OpenAlexvenueno aff
Holly S. J. Kearns, William R. Jacobi

Bibliographic record

VenueCanadian Journal of Forest Research · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicYeasts and Rust Fungi Studies
Canadian institutionsnot available
FundersDivision of Materials Research
KeywordsForestryEcologyGeographyInfestationCanopyBiologyBotany

Abstract

fetched live from OpenAlex

A survey of limber pine ( Pinus flexilis James) to determine the geographic distribution, incidence, and severity of white pine blister rust (WPBR) throughout 13 study areas in central and southeastern Wyoming and northern Colorado was conducted from 2002 to 2004. The majority (81.1%) of the 18 719 surveyed limber pines >1.37 m tall were classified as healthy, 13.5% were declining or dying from various causes, and 5.4% were dead. WPBR was present on 278 (55%) of the 504 survey plots. Incidence of the disease ranged from 0% to 100% and averaged 15.5% over all the plots and 28.0% on the infested plots. Likelihood of infection by WPBR was significantly greater for limber pines in larger diameter classes. Incidence was negatively correlated with elevation and positively correlated with geographic position, with more northerly and easterly plots having higher incidences of WPBR. Incidence varied by slope position and did not vary by aspect, slope configuration, or degree of canopy closure. The current level of infestation in central and southeastern Wyoming and northern Colorado has been attained within the past two to four decades. With time, the pathogen may spread to currently uninfested white pine populations and intensify throughout its current distribution impacting valuable ecosystems.

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)0.000
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 score0.528
Threshold uncertainty score0.951

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.281
Teacher spread0.264 · 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

Citations52
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Forest ResearchSame topicYeasts and Rust Fungi StudiesFrench-language works237,207