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Development of a Sustainability Evaluation System for Culvert Replacement and Rehabilitation Projects

2018· article· en· W2792275904 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Pipeline Systems Engineering and Practice · 2018
Typearticle
Languageen
FieldEngineering
TopicUnderground infrastructure and sustainability
Canadian institutionsGolder Associates (Canada)Queen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCulvertSustainabilityEngineeringRehabilitationConstruction engineeringCivil engineeringTransport engineeringBusinessForensic engineeringGeotechnical engineeringMedicinePhysical therapy

Abstract

fetched live from OpenAlex

As the number of deteriorated infrastructure assets, including culverts, continues to rise, there is a need to find the most cost-effective approaches to dealing with these assets. At the same time, there is a growing awareness that decisions cannot be made exclusively based on cost and that sustainability must also be considered. Although there exist a number of tools that allow environmental, societal, economic, and technical considerations to be assessed when evaluating alternatives for many infrastructure projects, there is no such tool for culverts. This paper describes the development of a culvert module for a commercially available assessment tool known as GoldSET. The environmental, societal, economic, and technical indicators used within the culvert module are introduced and described. The use of the tool is then demonstrated using two case studies that assess the viability of a traditional open-cut approach compared to trenchless approaches. For the two selected case studies, the trenchless approaches are found to be preferable except if considerations of technical uncertainties dominate the decision making.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.405
Threshold uncertainty score0.526

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.281
Teacher spread0.268 · 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