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Record W1491568305

Use and production of solid sawn timbers in the United States

2001· article· en· W1491568305 on OpenAlexaboutno aff
Gerry. Jackson, James L. Howard, A.L. Hammett

Bibliographic record

VenueForest Products Journal · 2001
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsnot available
Fundersnot available
KeywordsOriented strand boardspliceStructural engineeringJoint (building)EngineeringComposite materialEngineered woodStiffnessLaminated veneer lumberTension (geology)BendingMaterials scienceUltimate tensile strength
DOInot available

Abstract

fetched live from OpenAlex

Glued splice joints containing oriented strandboard (OSB) and lumber members were tested in tension in an attempt to develop joint reduction factors for OSB-to-OSB and OSB-to-lumber glued splice joints. OSB panels of two thicknesses were obtained from two manufacturers. Lumber was dry, dressed eastern Canadian spruce dimension lumber. The glue used was a resorcinol-formaldehyde adhesive, which meets the Canadian requirements for manufacturing structural wood products. In total, 360 single-splice joints, 450 double-splice joints, and 60 unjointed specimens were tested in tension. For OSB-to-OSB joints made with the thicker panels, the strength reduction is larger than those made with the thinner panels for the same splice length. However, for single-splice joints containing lumber as the main member, the greater lumber stiffness compared with OSB leads to smaller joint strength reduction because of the smaller bending deformation in the joint. Based on the test results, it is noted that at the mean strength level, a zero strength reduction is possible for some double-splice joints. However, a conservative reduction factor that varies between 0.65 to 0.9 for double-splice joints and 0.4 to 0.75 for single-splice joints was proposed for design use. These values have been adopted for structural design purposes in Canada.

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 score0.367
Threshold uncertainty score0.200

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 head0.029
GPT teacher head0.220
Teacher spread0.191 · 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

Citations4
Published2001
Admission routes1
Has abstractyes

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