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Record W2772352960 · doi:10.1520/jte20160297

A Test Protocol for Evaluating Absorption of Joints in Concrete Pavements

2017· article· en· W2772352960 on OpenAlexaffabout
Mohammad Tiznobaik, M. T. Bassuoni

Bibliographic record

VenueJournal of Testing and Evaluation · 2017
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsDurabilityMercury intrusion porosimetryMaterials scienceAbsorption of waterAbsorption (acoustics)Joint (building)IntrusionProtocol (science)Environmental scienceComposite materialStructural engineeringGeologyEngineeringPorosityPorous medium

Abstract

fetched live from OpenAlex

Abstract Premature deterioration at joint spresents a critical durability issue of concrete pavements associated with considerable repair costs. Durability of concrete exposed to aggressive environments depends mainly on the penetrability of its pore structure. Because absorption has been used as an important indicator for quantifying the durability of concrete, the aim of this study was to develop a customized test protocol for determining the absorption capacity of joints in concrete pavements. The study involved three phases with thorough statistical analyses of results. In Phase I, different absorption procedures were applied to laboratory specimens prepared with water-to-binder ratios (w/b) of 0.3, 0.5, and 0.6, representing variable qualities of concrete. The most efficient procedure was identified from Phase I and further verified in Phase II on concrete specimens prepared with a close range of w/b (0.35 and 0.40). In Phase III, the performance of the absorption protocol selected from the previous phases was assessed on cores extracted from recently constructed pavement sections in Winnipeg, Manitoba, Canada. To further complement and verify the trends obtained from the absorption protocol, mercury intrusion porosimetry tests were conducted on the field cores to capture the characteristics of the pore structure. The results indicated that the proposed absorption protocol was efficient, robust, and reliable in reflecting the physical features of the microstructure of field pavement sections, including joint locations.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.216
GPT teacher head0.442
Teacher spread0.226 · 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 designNot applicable
Domainnot available
GenreProtocol

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

Citations22
Published2017
Admission routes2
Has abstractyes

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