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Record W2011226732 · doi:10.1139/x11-161

Anatomical and chemical factors affecting tensile growth stress in <i>Eucalyptus grandis</i> plantations at different latitudes in Brazil

2011· article· en· W2011226732 on OpenAlexvenueno aff
Miho Kojima, Hiroyuki Yamamoto, Koichiro Saegusa, Fábio Minoru Yamaji, Masato Yoshida, Saori Yamashita, Takahisa Nakai

Bibliographic record

VenueCanadian Journal of Forest Research · 2011
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsnot available
Fundersnot available
KeywordsEucalyptusCelluloseLatitudeUltimate tensile strengthLigninMaterials scienceHorticultureComposite materialBotanyEnvironmental scienceBiologyGeography

Abstract

fetched live from OpenAlex

The key to using planted Eucalyptus as timber lies in controlling the characteristic high tensile growth stress that often causes serious processing defects in sawn logs and lumber. In the present study, we investigated variations in the longitudinal released strain (RS) of surface growth stress in stems of Eucalyptus grandis W. Hill ex Maiden planted in a wide range of latitudes in Brazil and established relationships between RS measurements and anatomical and chemical factors. Cellulose and lignin content, RS, and the microfibril angle (MFA) of the middle layer of the secondary wall (S 2 layer) differed among latitudes. The increase in cellulose content and decrease in MFA were correlated with the contractive value of RS, which explained the higher tensile growth stress in stems from high-latitude plantations where higher cellulose content and lower MFA were observed. To reduce processing defects due to tensile growth stress, the factors controlling MFA values and cellulose content must be identified.

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)0.000
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 score0.440
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.049
GPT teacher head0.265
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 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

Citations14
Published2011
Admission routes1
Has abstractyes

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