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Record W2183087521

Vulnerability to Climate Change Assessment for a Highway Constructed

2012· article· en· W2183087521 on OpenAlexaboutno aff
Janice Seto

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicSmart Materials for Construction
Canadian institutionsnot available
Fundersnot available
KeywordsPermafrostClimate changeVulnerability (computing)LeveeEnvironmental scienceCulvertCivil engineeringFoundation (evidence)Vulnerability assessmentRoad surfaceForensic engineeringEnvironmental resource managementEngineeringGeotechnical engineeringGeographyGeologyComputer science
DOInot available

Abstract

fetched live from OpenAlex

The 93 km section of Highway 3 located between Behchoko (Rae-Edzo) and Yellowknife is located in an area with warm and discontinuous permafrost and variable ground ice contents. The highway was originally constructed as a gravel road in 1968. Between 1999 and 2006, the alignment for this section of highway was straightened and reconstructed, and the road surface chip-sealed. To date, this section of highway has experienced significant sagging in soil-covered areas and requires considerable maintenance efforts to keep the road in a comfortable and safe driving condition. Embankment deformations have been attributed to the degradation of the ice-rich permafrost foundation. The Public Infrastructure Engineering Vulnerability Committee (PIEVC), a national committee established by Engineers Canada, has developed a standardized protocol to assess the vulnerability of Canada's public infrastructure to climate change. The protocol continues to be tested on a variety of public infrastructures and in 2010, this section of highway was evaluated as a case study. More than 1100 highway infrastructure element - climate event combinations were assessed. Out of these combinations, five were identified as high risk. The assessment identified those sections of the highway built on ice-rich permafrost as being at greatest risk, based on its low capacity to withstand the projected or anticipated climate-change related loads. Overall, the road embankment stability was found to be insensitive to climate change such that only functionality losses are expected, not sudden losses in capacity. Climate change will likely increase maintenance and repair efforts needed to maintain safe driving conditions.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.029
GPT teacher head0.293
Teacher spread0.264 · 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 teacher head, not a consensus.

Study designObservational
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

Citations0
Published2012
Admission routes1
Has abstractyes

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