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Record W1846968508 · doi:10.22230/jem.2008v9n2a397

British Columbia's Southern Interior Forests Armillaria Root Disease Stand Establishment Decision Aid

2008· article· en· W1846968508 on OpenAlexaffabout
Michelle Cleary, Bart van der Kamp, D. J. Morrison

Bibliographic record

VenueJournal of Ecosystems and Management · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsCanadian Forest ServiceUniversity of British ColumbiaGovernment of British Columbia
Fundersnot available
KeywordsArmillariaSilvicultureBiologyAgroforestryForestryEcologyGeographyBotany

Abstract

fetched live from OpenAlex

In the Southern Interior of British Columbia, Armillaria (Armillaria ostoyae) root disease (DRA) causes considerable losses in immature stands by killing natural and planted coniferous trees. Tree mortality usually begins about 5–7 years after stand establishment, peaks around age 12, and then declines, although mortality can continue throughout a rotation. On the roots of older trees, repeated non-lethal infections will result in growth loss. The disease also increases the susceptibility of trees to attack by other pathogens and insects. DRA poses a long-term threat to forest productivity and sustainable forest management because current silviculture practices increase the amount and potential of Armillaria inoculum and put regenerated or residual trees at risk of becoming infected. This threat can be moderated by planting trees that are more resistant to Armillaria or by modifying silviculture practices to minimize exposure of trees to Armillaria inoculum in managed, secondgrowth stands. This extension note provides a revised table of host susceptibility ratings for species as well as a decision key to help natural resource managers choose from among several different treatments.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.091
Threshold uncertainty score0.183

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 studies0.0030.000
Scholarly communication0.0020.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0270.002

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 head0.009
GPT teacher head0.191
Teacher spread0.182 · 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

Citations19
Published2008
Admission routes2
Has abstractyes

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