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Record W575435571

Pull-out strength properties of Lagscrewbolt connection for CLT construction

2014· article· en· W575435571 on OpenAlexfundno aff
Takuro Mori, Hiroshi Isoda, Akihisa Kitamori

Bibliographic record

VenueKyoto University Research Information Repository (Kyoto University) · 2014
Typearticle
Languageen
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsConnection (principal bundle)MathematicsGeometry
DOInot available

Abstract

fetched live from OpenAlex

With the availability of new engineered wood products such as cross laminated timber (CLT), it becomes possible to build a wide variety of wooden construction of frame structures of large height and long span.One of the most important design aspects for these structures is the connection.The lagscrewbolt (LSB) was first developed by Komatsu [1] as a rigid connector for wooden structures.A lot of the research was done with a focus on use of LSB in glulam construction.This study was aimed at examining the structural performance of a single or double LSBs inserted into CLT in terms of the insertion direction, the edge distance, and the distance of both LSBs.In Figure 1 was shown the LSB and CLT.The several parameter's specimens were tested for evaluating this aims.In this report, many types of specimens were used to examine the effect of edge distance, grain direction and multiple LSBs.It could be concluded as follows:

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.300
Threshold uncertainty score0.841

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.002
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 head0.021
GPT teacher head0.206
Teacher spread0.184 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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