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Record W1669155311 · doi:10.1061/9780784479315.054

Effect of Climate Changes Expected during Winter on Pavement Performance

2015· article· en· W1669155311 on OpenAlexaffabout
Jean-Pascal Bilodeau, François Perron Drolet, Guy Doré, Marie-France Sottile

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsFrost (temperature)Environmental scienceCold climateClimate changeAsphaltDeformation (meteorology)Geotechnical engineeringClimatologyGeologyMeteorologyMaterials scienceGeography

Abstract

fetched live from OpenAlex

In the coming decades, climate change will have significant impacts on the long-term performance of the road network of Quebec, particularly during winter periods. This study quantifies the effect of climate change expected in winter, specifically focusing on the effect of a decrease in the freezing index and an increase in the number of winter thaw episodes. First, milder winter temperatures will have a positive impact by reducing pavement damage caused by frost heaves. Increased duration of life of about 6–17% is expected for the middle of the century due to milder winters. Also, an expected increase in the number of winter thaw events is likely to have a negative impact on pavements, increasing damages by permanent deformation in the granular base and by fatigue in the asphalt concrete layer. Triaxial tests were conducted to evaluate the performance on permanent deformation of different grain-size distribution of base materials subjected to repeated winter thaw. The triaxial tests concluded that by mid-century, flexible pavements in Québec will experience a 7 to 13% reduction in service life regarding permanent deformation during winter partial thaws.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.662
Threshold uncertainty score0.445

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 head0.016
GPT teacher head0.253
Teacher spread0.237 · 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 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
Published2015
Admission routes2
Has abstractyes

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