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Record W2110856845 · doi:10.1139/l07-104

Innovative seismic design of a post-tensioned concrete masonry houseThis article is one of a selection of papers published in this Special Issue on Masonry.

2007· article· en· W2110856845 on OpenAlexvenueno aff
Gavin Wight, Jason Ingham, Andrew Wilton

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2007
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsnot available
FundersNorth Carolina Department of Transportation
KeywordsMasonryUnreinforced masonry buildingEngineeringCivil engineeringConstruction engineeringForensic engineeringArchitectural engineeringStructural engineering

Abstract

fetched live from OpenAlex

Post-tensioned concrete masonry walls provide improved seismic performance, but have had limited application in seismic regions because of a lack of research pertaining to their in-plane response. Following focused research over recent years, a consortium of product suppliers has collaborated with the University of Auckland to construct New Zealand’s first post-tensioned concrete masonry house. A feature of this innovative design was that all incorporated products were commercially available, with no proprietary products being specifically developed for the prestressed masonry system used. Consequently, it is hoped that this house will be a showcase, and provide exposure for the technology in New Zealand and elsewhere. This paper provides a brief review of previous post-tensioned concrete masonry research applications, then discusses post-tensioning details and their application to house design and construction.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.009
GPT teacher head0.190
Teacher spread0.181 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations16
Published2007
Admission routes1
Has abstractyes

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