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Record W2175893723 · doi:10.1139/cjce-2014-0466

Critical reaction forces of glulam members with tension-side notches at end supports

2015· article· en· W2175893723 on OpenAlexaffvenue
Jan Weckendorf, Henry Meleki Kiwelu, Ian F. C. Smith

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2015
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsTension (geology)BendingStructural engineeringMaterials scienceFracture (geology)Fracture mechanicsComposite materialEngineeringUltimate tensile strength

Abstract

fetched live from OpenAlex

Tests were carried out on softwood structural glued-laminated-timber (glulam) members to calibrate a linear elastic fracture mechanics design method for bending members having tension-side end notches. Fifty-eight specimens with depths up to 646 mm represented 11 combinations of member size, notch depth, member geometry, loading arrangement, and glulam type. Specimens were loaded until they sustained significant damage at or near notch locations, but none of them failed as bending members. Notch damage started with creation of short stable cracks parallel to the laminations and ended with episodically crack growth. Typically, crack initiation is at about half the load level associated with episodic crack growth. Contrary to current design practice loads positioned close to notched end supports were found to influence strengths of members significantly, and their effects should be taken into account. The findings have been implemented in the 2014 edition of CAN/CSA Standard 086 “Engineering Design in Wood”.

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)0.003
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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.013
GPT teacher head0.184
Teacher spread0.170 · 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

Citations3
Published2015
Admission routes2
Has abstractyes

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Same venueCanadian Journal of Civil EngineeringSame topicWood Treatment and PropertiesFrench-language works237,207