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Record W2139327782 · doi:10.1139/x05-307

Effects of precommercial thinning on tree growth and lumber quality in a jack pine stand in New Brunswick, Canada

2006· article· en· W2139327782 on OpenAlexaffvenueabout
S Y Zhang, Gilles Chauret, D. Edwin Swift, Isabelle Duchesne

Bibliographic record

VenueCanadian Journal of Forest Research · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsNatural Resources CanadaCanadian Forest Service
Fundersnot available
KeywordsThinningJack pineForestryPinus <genus>HorticultureSoftwoodPaulowniaMathematicsBotanyBiologyGeography

Abstract

fetched live from OpenAlex

A naturally regenerated jack pine (Pinus banksiana Lamb.) trial established in 1966 in New Brunswick was studied to determine how three precommercial thinning intensities (1.22 m × 1.22 m, 1.52 m × 1.52 m, and 2.13 m × 2.13 m) and a control (154 trees in total) affected tree growth and lumber quality. Mild (thinned to 1.22 m) and moderate (1.52 m) thinning had a modest impact on tree growth after 34 years (stand age 59). However, intensive thinning (2.13 m, or 2212 stems/ha) increased tree height by 13.1% compared with the control, whereas tree diameter and merchantable stem volume per tree increased by &gt;20% and &gt;75%, respectively. Yields of No. 2 and Better increased slightly with increasing thinning intensity, but lumber bending properties decreased with increasing thinning intensity. There was, respectively, &gt;20% and &gt;15% difference in lumber strength (modulus of rupture) and stiffness (modulus of elasticity) between the mild (1.22 m) and intensive (2.13 m) thinnings. Intensive precommercial thinning (2.13 m) is recommended for increased volume growth, but rotation age (&gt;59 years) should not be reduced if lumber bending properties are of concern.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.507

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.278
Teacher spread0.261 · 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 teacher head, 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

Citations74
Published2006
Admission routes3
Has abstractyes

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