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Record W2004170337 · doi:10.1139/l07-112

Sustainable precast concrete foundation system for residential construction

2008· article· en· W2004170337 on OpenAlexafffundvenueabout
Haitao Yu, Mohamed Al‐Hussein, Reza Nasseri, Roger Cheng

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsAlberta Conservation AssociationUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsConstructabilityPrecast concreteEngineeringCivil engineeringFoundation (evidence)Framing (construction)Construction engineeringArchitectural engineeringStandardizationStructural systemExpanded polystyreneStructural engineeringComputer science

Abstract

fetched live from OpenAlex

Residential construction has changed little in decades. In North America, houses are constructed predominantly with cast-in-place (CIP) concrete basement foundations and “custom-built” wood platform – framing structures. To improve the productivity of residential construction, a precast concrete foundation (PCF) system was developed by the University of Alberta and its industrial partners. Although the PCF system can be built much faster and better than conventional CIP foundations, it has not been considered a viable alternative in residential construction due to the belief that it is costly and less flexible. To overcome this perception, special research efforts were made to address issues of manufacturability, constructability, and standardization. This paper proposes an innovative design of the PCF system that satisfies functional requirements, while obtaining a minimum total cost and achieving flexibility. The unique features include a modularized rib structure, external insulation, and simplified bolted connections. A comparative analysis between PCF and traditional CIP concrete foundation systems is also presented.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.002

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 head0.007
GPT teacher head0.170
Teacher spread0.164 · 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

Citations12
Published2008
Admission routes4
Has abstractyes

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