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Record W4411656554 · doi:10.51847/krcprfl9pj

10.51847/kRCPRfl9Pj

2000· article· en· W4411656554 on OpenAlexvenueno aff

Bibliographic record

VenueTime to knit · 2000
Typearticle
Languageen
FieldEngineering
TopicStructural Analysis and Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsStructural engineeringGeologyEngineeringGeotechnical engineeringArchitectural engineering

Abstract

fetched live from OpenAlex

These days buildings are designed to support life safety performance level.Widespread damage caused by severe earthquakes due to permanent displacements in buildings, requires a great deal of time and effort to rebuild and rehabilitate these buildings.low damage systems classified in the category of inactive control systems are responsible for controlling permanent displacements and distribution of faults in the structure.In these systems, with the help of energy dissipation systems and pre-stressed cables, it is attempted to direct the damages to predetermined locations in the structure.In this paper, the seismic performance of different systems with rocking shear walls using pre-tensioned cables and dampers in the structure is examined with the view of improving the existing structure, and their performance is compared to the conventional use of fixed shear walls.By Using nonlinear dynamics analysis, we will examine various parameters in a twodimensional frame with rocking systems.The results obtained in this study indicate that rocking systems are better suited rather than conventional systems used in terms of performance and other important parameters in structural responses and can be used as an alternative retrofit scheme.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.059
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.9410.958

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 head0.003
GPT teacher head0.143
Teacher spread0.140 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2000
Admission routes1
Has abstractyes

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