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Record W646416339

Evaluation of Joint and Crack Sealant Based on Cyclic Loading and Rheological Properties

2007· article· en· W646416339 on OpenAlexaff
Haithem Soliman, Ahmed Shalaby

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicInfrastructure Maintenance and Monitoring
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsSealantService lifeJoint (building)Reliability (semiconductor)Forensic engineeringEngineeringEnvironmental scienceGeotechnical engineeringCivil engineeringReliability engineeringMaterials scienceComposite material
DOInot available

Abstract

fetched live from OpenAlex

Sealing pavement joints and cracks is one of the essential pavement maintenance practices to protect subsurface layers from the ingress of moisture and debris. In-service temperature range can be considered the most important factor affecting the expected life of a sealant. Using inappropriate crack sealant reduces its expected life which leads to reducing pavement design life. Development of a reliable characterization method for crack sealants has been a challenging process in the last decade. Currently, field studies are the most reliable method to evaluate sealants performance in cold climates which is not a cost-effective method. This research discusses two laboratory tests that were used for characterizing the performance of hot-pour sealants in cold climates. The results of a two years field study were used to verify the reliability of these methods. These laboratory methods can replace costly and time-consuming field studies, and provide the ability to test and evaluate the performance of new sealing materials as they become available in market. For the covering abstarct of this conference see ITRD number E216511.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.412
Threshold uncertainty score0.176

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 science0.0000.000
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 head0.036
GPT teacher head0.241
Teacher spread0.205 · 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

Citations3
Published2007
Admission routes1
Has abstractyes

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