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Record W2949304868

Evaluation on dynamic performance of glulam frame structure composed of slotted bolted connection system

2014· article· en· W2949304868 on OpenAlexaboutno aff
Kohei Komatsu, Takuro Mori, Akihisa Kitamori, Yasuhiro Araki

Bibliographic record

VenueKyoto University Research Information Repository (Kyoto University) · 2014
Typearticle
Languageen
FieldEngineering
TopicTree Root and Stability Studies
Canadian institutionsnot available
FundersJapan Society for the Promotion of Science
KeywordsStructural engineeringFrame (networking)Bolted jointConnection (principal bundle)Steel frameFinite element methodEngineeringMechanical engineering
DOInot available

Abstract

fetched live from OpenAlex

Earthquake-resisting performance of glulam frame structure was evaluated by shaking table tests on a specially designed glulam “double cross shape” specimen composed of slotted bolted connection (SBC) system. By the first vibration test using sinusoidal wave having a maximum acceleration of 800gal, the specimen survived until 80% level of input waves without damage. After renewing SBC system, the second vibration test was done on a same specimen using the JMA-Kobe NS waves having a PGA of 818gal. The specimen survived until 80% level of input without damage but slightly failed by the panel-shear when 100% level was inputted. Earthquake-resisting performance of glulam moment-resisting joints composed of SBC system was considered as satisfactory enough for ductile joint system, but improvement of panel-shear of glulam member itself was recognized as a future research need.

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)0.001
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 score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.216
Teacher spread0.203 · 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

Citations8
Published2014
Admission routes1
Has abstractyes

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