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Record W3157248808 · doi:10.5558/tfc2020-021

Evaluating the 3-m tree crown spacing guideline for the prevention of crowning wildfires in lodgepole pine forests, Alberta

2020· article· en· W3157248808 on OpenAlexvenueaboutno aff
Martin E. Alexander, Miguel G. Cruz

Bibliographic record

VenueThe Forestry Chronicle · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsCrown (dentistry)Pinus contortaCanopyThinningForestryEnvironmental scienceTerrainTree canopyGeographyCartographyArchaeologyMaterials science

Abstract

fetched live from OpenAlex

A 3-m between crown spacing is a commonly cited criterion found in the wildland-urban interface fire literature for minimizing the likelihood of a fully-developed crown fire from occurring in a conifer forest on level terrain. The validity of this general recommendation is examined here in light of our current state-of-knowledge regarding crown fire propagation in relation to canopy bulk density. Given the characteristics of the overstory structure for 20 lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.) stands located in Alberta, as sourced from the literature, the canopy fuel properties following a virtual thinning to a 3-m crown spacing and then to a targeted canopy bulk density of 0.05 kg/m3 were computed. On the basis of these computations, crown fire potential was then analyzed and interpreted. The conclusion reached is that, in the majority of cases, a less widely spaced stand would be adequate for preventing crown fire development in lodgepole pine forests.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.586
Threshold uncertainty score0.822

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.033
GPT teacher head0.308
Teacher spread0.275 · 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
Published2020
Admission routes2
Has abstractyes

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