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Record W1497303021

Comparing the potential of acoustic parameters for the assessment of the strength of timber

2011· article· en· W1497303021 on OpenAlexvenueno aff
Roderick C. I. MacKenzie, Charles Fairfield, R. Sean Smith

Bibliographic record

VenueCanadian acoustics · 2011
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsnot available
FundersScottish Funding Council
KeywordsBeam (structure)Nondestructive testingMaterials scienceHomogeneity (statistics)DrillingAcoustic emissionHarmonicStructural engineeringVeneerAcousticsUltrasonic sensorComposite materialEngineeringMathematicsPhysics
DOInot available

Abstract

fetched live from OpenAlex

The article compares the potential of acoustic parameters for the assessment of the strength of timber. Acoustic NDT parameters were evaluated during tests on 33 controlled-homogeneity beam specimens cut from 12-layer laminated veneer panels and three solid wood beams. The LF and ultrasonic TOF velocities were also measured. Holes were then drilled through the beams and filled with dowels to simulate knots. These holes were then re-drilled and larger dowels inserted. The number of 25 mm simulated knots was progressively increased along the beam while avoiding drilling at the anti- nodal positions of the eighth harmonic. The eighth harmonic underwent little change until holes were drilled at its anti- nodal points because harmonic frequencies are derived, not from a measurement of the whole specimen, but from discrete points along it.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.034
GPT teacher head0.210
Teacher spread0.177 · 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 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

Citations0
Published2011
Admission routes1
Has abstractyes

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