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Record W2220120672 · doi:10.5558/tfc2015-047

The moisture content and opening of serotinous cones from lodgepole pine killed by the mountain pine beetle

2015· article· en· W2220120672 on OpenAlexafffundvenueabout
Maria Sharpe, Soung Ryoul Ryu

Bibliographic record

VenueThe Forestry Chronicle · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsGovernment of AlbertaUniversity of Alberta
FundersUniversity of Alberta
KeywordsWater contentMountain pine beetleEnvironmental scienceForestryBotanyBiologyGeographyGeology

Abstract

fetched live from OpenAlex

The aging lodgepole pine forests of Western Canada have become increasingly susceptible to insect and disease outbreaks. This is evident by the rise of mountain beetle (MPB) populations in British Columbia and Alberta. Serotinous cones of lodgepole pine require heat to open and the moisture content (MC) of cones is considered to influence the opening process. However, little is known about how tree conditions (live and dead) may affect this process. We evaluated the effects of MPB-killed trees and cone age on (1) cone MC, (2) moisture exchange, and (3) time required to open a cone after exposure to heat. The results showed active moisture exchange into and out of closed cones from both live and dead trees. Cone MC was not a main driving factor determining the time for opening the cones. Cones from dead trees had higher mean moisture content (MC), higher MC variation and took a longer time to open than those from live trees, presumably decreasing the potential for scorching of seed supply. This indicates that seeds in cones of MPB-killed stands may be better able to survive a fire than those of live trees.

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 score0.026
Threshold uncertainty score0.051

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 communication0.0010.000
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 head0.224
Teacher spread0.207 · 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

Citations2
Published2015
Admission routes4
Has abstractyes

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