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Record W7099609132

SUMMARY

2004· article· en· W7099609132 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsBracingSubstructureSeismic retrofitSeismic energyBridge (graph theory)SuperstructureDissipationVulnerability (computing)
DOInot available

Abstract

fetched live from OpenAlex

Seismic vulnerability assessments of many existing deck-truss bridges often reveals the vulnerability of their substructure and many superstructure members. As an alternative to costly strengthening of many components or seismic isolation, an innovative retrofit strategy developed which requires only replacement of the existing non-ductile end and lower-end bracing with ductile panels. By incorporating these energy dissipating devices acting as fuses, these devices can yield and dissipate energy while protecting both superstructure and substructure. A 27-ft long deck-truss bridge model was designed and constructed at the University of Ottawa and was pseudo-dynamically tested in its as-built as well as retrofitted conditions. Two configurations of Eccentrically Braced Frames, EBF, and Vertical Shear Links, VSL, were used as ductile retrofits, and both performed well. The ductile retrofit devices exhibited a robust hysteretic behavior, dissipated the seismic induced energy and prevented damage in other structural members of the model bridge when it was subjected to scaled El Centro earthquake. This paper describes the retrofit concept, the innovative seismic testing procedure, and the performance of the steel ductile retrofits.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.499
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.5010.333

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 head0.208
Teacher spread0.196 · 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.

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
Published2004
Admission routes1
Has abstractyes

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