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Record W2172404537 · doi:10.1139/x11-038

Variation in wood density components within and between <i>Quercus faginea</i> trees

2011· article· en· W2172404537 on OpenAlexvenueno aff
Sofia Knapic, José Louzada, Helena Pereira

Bibliographic record

VenueCanadian Journal of Forest Research · 2011
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsnot available
FundersFundação para a Ciência e a Tecnologia
KeywordsPithCambiumBotanyCoefficient of variationBark (sound)BiologyHorticultureMathematicsXylemEcology

Abstract

fetched live from OpenAlex

The wood of Quercus faginea Lam. was studied regarding its density variation within and between trees using microdensitometry techniques in 10 trees growing in northern Portugal. The observations were made in mature trees at several height levels (stem base and 1.3, 3.4, 5.5, 7.6, and 9.7 m). Variance analysis was done considering the core cylinder (first 15 rings) and the sheath (last 10 rings) in relation to tree, height level, and ring effects and their interactions. The wood revealed a high mean density of 0.848 g·cm –3 with small differences between earlywood and latewood (0.717 and 0.908 g·cm –3 , respectively). Latewood corresponded on average to 66% of the total ring width, which averaged 2.4 mm. Wood density decreased with height and radially from pith to cambium. However, within-tree variation was of very moderate magnitude although higher for juvenile wood. Variation between trees was also small (6% coefficient of variation of the mean) and higher for the mature wood. Quercus faginea wood compares favourably with other oak species with regard to density characteristics and may be considered for production of quality solid wood products.

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 score0.238
Threshold uncertainty score0.984

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 head0.094
GPT teacher head0.255
Teacher spread0.160 · 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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