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Record W2168096551

Mechanistic Investigation of Granular Base and Subbase Materials A Saskatchewan Case Study

2004· article· en· W2168096551 on OpenAlexaffabout
Curtis Berthelot, Allan Widger, T Gehlen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsSubbaseEnvironmental scienceEngineeringCivil engineeringGeotechnical engineeringGranular materialRoad constructionTransport engineeringForensic engineeringMathematics
DOInot available

Abstract

fetched live from OpenAlex

Saskatchewan Department of Highways and Transportation (DHT) commonly specify three types of subbase course and three types of base course materials for conventional road building. These specifications are primarily based on grain size and were developed years ago at a time of lower variation in pit run quality. Today, DHT are experiencing reduced pit run availability and increased variability in pit run quality, especially with respect to fines content. This is resulting in higher pit wastage and with the increased opportunity for undesirable material, there is a higher risk for varied performance in the field. At the same time, traffic loadings have exceeded the original safety margin incorporated into the empirical based granular specifications used today. This study investigated a mechanistic characterization protocol of typical DHT specified granular materials to quantify any significant difference that exist may in the mechanistic behaviour as a function of fines content, moisture content and cement modification. For the covering abstract of this conference see ITRD number E211395.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.400

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 head0.018
GPT teacher head0.234
Teacher spread0.216 · 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

Citations8
Published2004
Admission routes2
Has abstractyes

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