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Record W2063339274 · doi:10.1515/hf.2011.053

Relationships between mechanical properties of oak timber (Quercus robur L.)

2011· article· en· W2063339274 on OpenAlexfundno aff
Guillermo Riesco Muñoz, Andrés Remacha Gete

Bibliographic record

VenueHolzforschung · 2011
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsnot available
FundersUniversidade de Santiago de CompostelaXunta de GaliciaUniversity of Manitoba
KeywordsMaterials scienceFlexural strengthBendingComposite materialStiffnessQuercus roburCompression (physics)SoftwoodYoung's modulusPorosityHardwoodBending stiffnessCompressive strengthMathematicsStructural engineeringBotanyEngineering

Abstract

fetched live from OpenAlex

Abstract Ring-porous hardwoods such as oak are in high demand for furniture-making, cooperage, flooring, and construction. However, evaluating the quality of such timber is difficult and time consuming, and simpler tests are required. Models for predicting as many mechanical properties as possible, based on easier-to-determine mechanical tests, may help. In this study, the hardness, modulus of elasticity, bending, compression, and impact bending strength parallel to grain were tested on defect-free laths obtained from a sample of 42 oak trees. The relationships between the variables were investigated. Three models that relate the resistance to axial compression with bending strength and stiffness (R 2 >0.55; P<0.01) are proposed for defect-free oak timber. Selection of models mainly depended on the bias, which was highly variable among the models tested. The prediction models proposed in the international standard EN 384:2004 for structural dimension timber are not suitable for small clear wood specimens, especially in very elastic woods. The relative independence of hardness and impact bending strength as regards the other mechanical properties is also demonstrated.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.668
Threshold uncertainty score0.466

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.132
GPT teacher head0.194
Teacher spread0.062 · 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 designBench or experimental
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

Citations10
Published2011
Admission routes1
Has abstractyes

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