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Record W2068033101 · doi:10.5558/tfc2013-141

Wildfire’s resistance to control in mountain pine beetle-attacked lodgepole pine forests

2013· article· en· W2068033101 on OpenAlexaffvenue
Wesley G. Page, Martin E. Alexander, Michael J. Jenkins

Bibliographic record

VenueThe Forestry Chronicle · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsUniversity of Alberta
FundersJoint Fire Science Program
KeywordsMountain pine beetlePinus contortaDendroctonusResistance (ecology)Crown (dentistry)EcologyGeographyOutbreakForestryEnvironmental scienceAgroforestryBark beetleBiologyBark (sound)

Abstract

fetched live from OpenAlex

Concerns about the impacts of mountain pine beetle (Dendroctonus ponderosae Hopkins)-caused tree mortality on wildfire potential in lodgepole pine (Pinus contorta Dougl. var. latifolia Engelm.) forests have to date largely focused on the potential for extreme fire behaviour, including the development and spread of crown fires. Given that the wildland fire environment in which fire managers and firefighters work is composed of many interacting physical and human factors, viewing crown fire behaviour as the only or even the most important outcome of the tree mortality associated with a mountain pine beetle outbreak is questionable. Proper assessment of wildfire potential entails a broader approach, which requires expanding the concept of wildfire resistance to control to include an analysis of all relevant factors and their interactions. In this paper we describe a holistic concept of analyzing the impacts of mountain pine beetle-caused tree mortality on wildfire potential in lodgepole pine forests on the basis of fire behaviour characteristics, fire suppression operations, and firefighter safety considerations within the framework of three recognizable stages of the approximate time since the initiation of an outbreak (i.e., “red” ∼1 to 5 years, “gray” ∼5 to 15 years, and post-epidemic ∼15+ years).

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.299
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.005

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 head0.005
GPT teacher head0.216
Teacher spread0.211 · 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; both teacher heads agree on what is shown here.

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

Citations56
Published2013
Admission routes2
Has abstractyes

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