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Record W2084265650 · doi:10.1139/l08-012

Laboratory study on the relative performance of treated granular materials used for unpaved roads

2008· article· en· W2084265650 on OpenAlexaffvenueabout
Pascale Pierre, Jean-Pascal Bilodeau, Glen Légère, Guy Doré

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsUniversité LavalFPInnovations
Fundersnot available
KeywordsCalifornia bearing ratioCompactionGeotechnical engineeringEnvironmental scienceCompression (physics)Materials scienceEngineeringComposite material

Abstract

fetched live from OpenAlex

Unpaved roads in Canada are subjected to high wheel loads and environmental factors that significantly affect their performance. As part of a larger research project, the objective of this laboratory study was to compare the relative performance of various stabilization and dust lifting resistance agents to an untreated granular material commonly used as a base and wear course on unpaved roads. The performance is compared using California bearing ratio (CBR), resilient modulus, and unconfined compression strength tests. In addition, the surface sealing potential was measured on each specimen. The effects of compaction water content, product concentration, and the environment were investigated in this study. The results show that these variables have a significant impact on the performance measured, and it was possible to identify peak performance concentrations and performing products for the conditions tested.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.210
Teacher spread0.190 · 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 source (direct Gemma or distilled Codex), 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
Published2008
Admission routes3
Has abstractyes

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Same venueCanadian Journal of Civil EngineeringSame topicAsphalt Pavement Performance EvaluationFrench-language works237,207