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Record W2321239103 · doi:10.1515/hf-2015-0008

Assessing the wood quality of interior spruce (<i>Picea glauca</i> × <i>P. engelmannii</i>): variation in strength, relative density, microfibril angle, and fiber length

2015· article· en· W2321239103 on OpenAlexaff
Shawn D. Mansfield, Roberta Parish, Peter K. Ott, James Foster Hart, James W. Goudie

Bibliographic record

VenueHolzforschung · 2015
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsMinistry of ForestsUniversity of British Columbia
Fundersnot available
KeywordsPithTracheidMicrofibrilDiameter at breast heightBark (sound)BotanyComposite materialPicea abiesYoung's modulusFiberMaterials scienceHorticultureBiologyEcology

Abstract

fetched live from OpenAlex

Abstract A dynamic interrelationship exists among wood density and fiber traits (tracheid length and microfibril angel, MFA) and the ultimate wood strength properties. Moreover, many of the basic fundamental wood attributes are heavily influenced by crown size and architecture. In an attempt to examine this interplay, we thoroughly characterized 60 interior spruce ( Picea glauca × P. engelmannii ) trees sampled in three age classes from four sites in central British Columbia. Breast height discs were taken, and relative wood density was measured along two radii. Tracheid length was assessed on isolated 5 years increments from pith to bark at breast height for each tree, as was MFA. Segmented regression was used to identify the “juvenile to mature wood” transition point, which revealed transition ages of 9.4 and 15.1 years for wood density and MFA, respectively, while fiber length continued to elongate until near 60 years of age. The flexural properties, modulus of elasticity (MoE) and modulus of rupture (MoR), were also quantified in the 60 individuals and found to be best predicted by V FV , a measure of tree vigor, and not the basic wood attributes. These findings imply that long crowns carrying large amounts of foliage, V FV , negatively impact wood strength in interior spruce.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.485
Threshold uncertainty score0.598

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 communication0.0000.001
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 head0.038
GPT teacher head0.275
Teacher spread0.236 · 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

Citations20
Published2015
Admission routes1
Has abstractyes

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