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Record W3155053003

Assessing the Impact of Curing on Chloride Penetration Resistance of the Concrete Cover Zone

2020· dissertation· en· W3155053003 on OpenAlexfundno aff
Majed Karam

Bibliographic record

VenueTSpace · 2020
Typedissertation
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsnot available
FundersMitacsUniversity of Toronto
KeywordsCuring (chemistry)Penetration (warfare)Composite materialMaterials scienceGeotechnical engineeringForensic engineeringEngineeringOperations research
DOInot available

Abstract

fetched live from OpenAlex

There is a lack of rapid test methods for accurately assessing the impact of curing on the differential hydration through the depth of the concrete cover as well as the impact on chloride penetration resistance. In the absence of adequate performance assessment tools, prescriptive curing specifications have been adopted for concretes exposed to chlorides and other exposures, such as in CSA A23.1-19. There is a desire to switch to a performance specifications for curing, particularly by the precast concrete industry, that could be used to assess the impact of using of accelerated heat curing methods widely used to obtain high early-strength gain and maturity. Two methods are presented and evaluated in this thesis. The first involves proling the initial rate of absorption of a sodium chloride solution. The second makes use of embedded arrays of electrodes to map the formation factor with depth, enabling a multi-mechanistic approach to the problem.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0020.001

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 head0.026
GPT teacher head0.354
Teacher spread0.328 · 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 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

Citations0
Published2020
Admission routes1
Has abstractyes

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