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Record W4246107393 · doi:10.24124/2011/bpgub721

Secondary stand structure and its timber supply implications for mountain pine beetle attacked forests on the Nechako Plateau of British Columbia.

2011· dissertation· en· W4246107393 on OpenAlexaboutno aff
John Pousette

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsSite indexForestryPlateau (mathematics)Stand developmentEnvironmental scienceBasal areaMountain pine beetleTerm (time)GeographyAgroforestryEcologyMathematicsBiologyPhysics

Abstract

fetched live from OpenAlex

Post-mountain pine beetle epidemic, secondary stand structure measured in 1370 mature leading pine plots in the central interior of British Columbia indicate significant levels of advanced regeneration (AR) in most Biogeoclimatic (BEC) subzones. Future growth of AR was predicted using SORTIE ND and VDYP7 natural stand growth and yield models with inputs such as species composition, diameter distribution, site index (BHA50), basal area and quadratic mean diameter. The SELES (STSM) spatially explicit landscape event simulation model forecasts timber supply incorporating AR focusing on alleviating predicted mid-term (15 to 60 year) fall-down. SELES forecasts incorporating AR using VDYP7 results in a 6% increase in mean mid-term harvest level for the Prince George Timber Supply Area. If SORTIE ND is used, mid-term forecast is increased by 23%. Additional scenarios show benefits to mid-term timber supply when stands with well developed AR are reserved for harvest until after the initial salvage period. --P.ii.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.100
Threshold uncertainty score0.201

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.011
GPT teacher head0.244
Teacher spread0.233 · 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
Published2011
Admission routes1
Has abstractyes

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