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Record W3213162578 · doi:10.1139/cjce-2021-0180

Investigation of climate change impacts on early-age cracking of jointed plain concrete pavements in Canada

2021· article· en· W3213162578 on OpenAlexaffvenueabout
Mohammad Shafiee, Omran Maadani

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsClimate changeEnvironmental scienceCrackingRelative humidityWind speedGlobal warmingClimatologyMeteorologyGeographyGeology

Abstract

fetched live from OpenAlex

Canada’s climate is warming at a rate about double the global average, leading to potential negative impacts on public infrastructures such as jointed plain concrete pavement (JPCP). In light of this reality of changing climate, the work contained in this paper is aimed at evaluating JPCP’s early-age behaviour in response to environmental conditions. HIPERPAV® software and the associated models developed by the U.S. Federal Highway Administration (FHWA) were used to identify cracking potential. A sensitivity analysis was performed to assess the effect of different levels of air temperature, mix temperature, base layer temperature, wind speed, and relative humidity. Additionally, projected extreme temperatures predicted by the Canadian Regional Climate Model (CanRCM) were used to determine the relative impact of climate change on cracking risk. The results demonstrated the increased cracking risk under changing climate in several Canadian cities by mid-century and highlighted the importance of developing a pathway forward for climate adaptation.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.827
Threshold uncertainty score0.882

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 head0.023
GPT teacher head0.207
Teacher spread0.184 · 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

Citations3
Published2021
Admission routes3
Has abstractyes

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