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Record W279076224

Impact of a Regeneration Method and Vertical Position on Juvenile Wood Properties of Jack Pine in Northwestern Ontario

2011· article· en· W279076224 on OpenAlexaboutno aff
Mathew Leitch, Chander Shahi, Karen Roberts Jackson

Bibliographic record

VenueWood and Fiber Science (Society of Wood Science and Technology) · 2011
Typearticle
Languageen
FieldEngineering
TopicTree Root and Stability Studies
Canadian institutionsnot available
Fundersnot available
KeywordsJack pineJuvenileRegeneration (biology)Forest regenerationYoung's modulusSeedingPinus <genus>Environmental scienceTaigaForestryBotanyBiologyAgronomyMaterials scienceGeographyEcologyAgroforestryComposite material
DOInot available

Abstract

fetched live from OpenAlex

The effects of regeneration methods and vertical positions on three juvenile wood properties of 25-yr-old jack pine grown in the Boreal forests of northwestern Ontario were studied. Modulus of elasticity and modulus of rupture in static bending and specific gravity were determined from clear wood specimens of three vertical positions of trees selected from four stands that were aerial-seeded, Bracke-seeded, planted, and postfire naturally regenerated. Juvenile wood properties among the four regeneration methods were not significantly different, however, they were found to vary significantly among the vertical positions for three of the methods: aerial-seeded, Brack-seeded, and postfire natural stands. The wood properties of juvenile jack pine were quite variable, irrespective of the regeneration method, but there is a substantial potential in separating jack pine logs along the stem for various uses based on the regeneration method.

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 score0.552
Threshold uncertainty score0.890

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 studies0.0010.000
Scholarly communication0.0000.000
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 head0.022
GPT teacher head0.238
Teacher spread0.216 · 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

Citations1
Published2011
Admission routes1
Has abstractyes

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