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Record W2113154214 · doi:10.3141/1991-13

Low-Temperature Characterization of Hot-Poured Crack Sealant by Crack Sealant Direct Tensile Tester

2007· article· en· W2113154214 on OpenAlexaff
Imad L. Al‐Qadi, Shih‐Hsien Yang, Samer Dessouky, J-F. Masson

Bibliographic record

VenueTransportation Research Record Journal of the Transportation Research Board · 2007
Typearticle
Languageen
FieldEngineering
TopicInfrastructure Maintenance and Monitoring
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsSealantCrumb rubberMaterials scienceUltimate tensile strengthComposite materialAsphaltTensile testingNatural rubberService lifeStructural engineeringForensic engineeringEngineering

Abstract

fetched live from OpenAlex

The current specifications for selecting crack sealants correlate poorly with actual field performance. To address this issue and assist in predicting the low-temperature properties of hot-poured bituminous crack sealants, a modified direct tensile tester method has been developed. Sample geometry is modified to accommodate testing sealants. A sensitivity analysis considering various loading rates, sample lengths, and cross-section areas was conducted to define both optimized specimen geometry and testing protocol. Two types of sealants, having a wide range of rheological behaviors (one polymer-modified and one having crumb rubber), were tested at low temperature. Results showed that the rich polymer–modified sealant has a high resistance to failure compared with the sealant with crumb rubber–modified. Each sealant was tested at the lowest corresponding expected service temperature. A performance parameter, strain energy density, was proposed to differentiate crack sealant material in the laboratory.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.620
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
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 head0.021
GPT teacher head0.300
Teacher spread0.280 · 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.

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

Citations15
Published2007
Admission routes1
Has abstractyes

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