MétaCan
Menu
Back to cohort
Record W837884637

Influence of the Mineral Nature and the Temperature of the Aggregate in the Water Resistance of Foam Bitumen Stabilized Mixes

2006· article· en· W837884637 on OpenAlexaboutno aff
J K Davidson, JM Croteau

Bibliographic record

Venue10TH INTERNATIONAL CONFERENCE ON ASPHALT PAVEMENTS - AUGUST 12 TO 17, 2006, QUEBEC CITY, CANADA · 2006
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsGradationAsphaltAggregate (composite)Materials scienceCrackingComposite materialRutCohesion (chemistry)Water resistanceMixing (physics)CoatingChemistry
DOInot available

Abstract

fetched live from OpenAlex

In-place foamed bitumen stabilization is experiencing a global growth worldwide. This pavement rehabilitation process was introduced in Canada in the early nineties. It is currently estimated that between two and three million square metres of pavement are rehabilitated using this method every year throughout Canada. Foamed stabilized mixtures have properties that differ significantly from those of standard hot bituminous mixtures. Contrary to hot bituminous mixes, the coating of the aggregate is selective and the voids in the mixture are high. Consequently, properties of foam-stabilized mixtures are closely associated with the aggregate skeleton of the mixture. In general, foam mixes are not as thermally sensitive as hot mix and their resistance to rutting and thermal cracking is excellent. However, the cohesion of foam mixes is significantly lower than hot mix which reduces their resistance to water damage. This paper focuses on the water resistance of in-place foamed bitumen stabilized mixes that have between 2.5 and 3.0 % added binder. The concepts associated with water resistance in relation to the temperature of the aggregate during mixing and the mineral nature/gradation of the aggregate are outlined. And finally, the paper provides results of testing of mixes produced using various water resistance enhancers.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.645
Threshold uncertainty score0.749

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.009
GPT teacher head0.227
Teacher spread0.219 · 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 designObservational
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
Published2006
Admission routes1
Has abstractyes

Explore more

Same venue10TH INTERNATIONAL CONFERENCE ON ASPHALT PAVEMENTS - AUGUST 12 TO 17, 2006, QUEBEC CITY, CANADASame topicAsphalt Pavement Performance EvaluationFrench-language works237,207