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Record W2804178656 · doi:10.1371/journal.pone.0196063

Single-generation effects on terpenoid defenses in lodgepole pine populations following mountain pine beetle infestation

2018· article· en· W2804178656 on OpenAlexafffundabout
Sharleen L. Balogh, Dezene P.W. Huber, B. Staffan Lindgren

Bibliographic record

VenuePLoS ONE · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsUniversity of Northern British Columbia
FundersBritish Columbia Knowledge Development FundUniversity of Northern British ColumbiaNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanada Foundation for InnovationMinistry of Environment
KeywordsMountain pine beetleSeedlingBiologyInfestationTerpenoidBotanyPinus contortaTerpeneHeritabilityMethyl jasmonateHerbivorePEST analysisHorticultureEcology

Abstract

fetched live from OpenAlex

The recent mountain pine beetle outbreak in western Canada provides an opportunity to study the selection and heritability of tree defenses. We examined terpenoid-based defenses of seedling lodgepole pines which were offspring of mature trees subjected to high levels of mountain pine beetle selective pressure. Seedlings were grown from one of three types of cones: old cones on live trees; young cones on live trees; and cones on trees killed by beetles. Offspring thus represented crosses of non-surviving (NS) x surviving (S), S x S, and NS x NS parents, respectively. Methyl jasmonate was used to induce a defensive reaction in the seedlings. Seed source had a significant effect on levels of ten different terpenes, but not on total terpene concentrations. When the seedlings were grouped by location and treatment type, the seedlings of different cone types could be almost entirely distinguished by terpene profiles.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.039
GPT teacher head0.242
Teacher spread0.203 · 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

Citations5
Published2018
Admission routes3
Has abstractyes

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Same venuePLoS ONESame topicForest Insect Ecology and ManagementFrench-language works237,207