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Record W4404352568 · doi:10.1139/cjce-2024-0260

The impact of projected Canadian regional climate model data on flexible pavement performance

2024· article· en· W4404352568 on OpenAlexafffundvenueabout
Omran Maadani, Mohammad Shafiee, Juan Hiedra Cobo

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicSmart Materials for Construction
Canadian institutionsNational Research Council Canada
FundersNational Research Council Canada
KeywordsEnvironmental scienceCivil engineeringComputer scienceTransport engineeringEngineering

Abstract

fetched live from OpenAlex

This paper explores the impact of projected climatic loading parameters, utilizing Environment and Climate Change Canada data, on flexible pavement performance and design. Despite the expectation that flexible roads should endure various structural and environmental conditions throughout their design life, premature damage often occurs within the initial 3–5 years of service. Therefore, understanding the impact of climate change on flexible pavements in the historical, short, intermediate, and long terms becomes crucial. The pavement mechanistic empirical design (PMED) was employed to assess climatic loading effects on pavement design and performance. PMED-predicted rutting performance showed sensitivity when comparing historical and projected climatic loading parameters up to 2093. Preliminary results based on a 25-year design life for City of Windsor revealed a 72% higher rutting impact compared to historical data, shortening the pavement's design life by 28%, 56%, and 68% for short, intermediate, and long terms, respectively.

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 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 score0.613
Threshold uncertainty score0.915

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)0.0000.000

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 head0.022
GPT teacher head0.229
Teacher spread0.207 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2024
Admission routes4
Has abstractyes

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