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Record W2532462028 · doi:10.11159/icsenm16.114

Bolt Slippage Evaluation in Column-tree Steel Moment Connection on L/d

2016· article· en· W2532462028 on OpenAlexvenueno aff
Kangmin Lee, Keunyeong Oh, Jaehyuk So

Bibliographic record

VenueProceedings of the World Congress on Civil, Structural, and Environmental Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicMechanical stress and fatigue analysis
Canadian institutionsnot available
FundersNational Research Foundation of KoreaMinistry of Science, ICT and Future PlanningNational Research Foundation
KeywordsSlippageConnection (principal bundle)Column (typography)Moment (physics)Tree (set theory)Structural engineeringMaterials scienceComputer scienceEngineeringMathematicsPhysicsCombinatorics

Abstract

fetched live from OpenAlex

The purpose of this paper was to evaluate the bolt slippage in column-tree steel moment connection.Column-tree connections are composed of a shop-welded and field-bolted steel structure.However, it is known for that the bolt slippage was occurred in columntree connection system.Therefore, the bolt slippage in column-tree connection was examined the effects on seismic performance.So, there are fabricated with that 600, 500, 400 mm depth of beam were attached to same column size, respectively.As a result, the maximum load obtained from column face was increasingly decreased when the depth of beam was smaller.Also, if it is possible to control the L/d, it would be determined the section and amount of bolt slippage.

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)0.000
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.008
GPT teacher head0.191
Teacher spread0.183 · 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
Published2016
Admission routes1
Has abstractyes

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