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Record W7132859030

Using Accelerated Testing to Indicate Later-Age Chloride Ingress and Bulk Resistivity of Concrete

2023· dissertation· W7132859030 on OpenAlexaff
Nour Taza

Bibliographic record

VenueTSpace · 2023
Typedissertation
Language
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsHudbay Minerals (Canada)
Fundersnot available
KeywordsCuring (chemistry)CementitiousDurabilityElectrical resistivity and conductivityPermeability (electromagnetism)ChlorideTest method
DOInot available

Abstract

fetched live from OpenAlex

Supplementary Cementitious Materials (SCMs) are used in concrete to help improve the durability of the hardened concrete and to reduce global warming potential. Ambient curing does not provide enough time for the SCMs to develop their potential by 28 days, as they typically require 91 days, as allowed in CSA A23.1. Use of optional accelerated curing allows for SCMs to develop more of their potential by 28 days and speed up evaluation for construction acceptance. This study aims to promote the use of accelerated curing for evaluation of SCM concretes in terms of strength, Rapid Chloride Permeability Test (RCPT), and Bulk Electrical Resistivity Test data. These tests were conducted on both cylinders and cores extracted from slabs on concrete mixtures with varying levels of SCMs. The results were then compared to determine if accelerated curing test data can be used for acceptance. The correlation between cylinder and core results are discussed, as well as the correlation between the RCP and bulk resistivity test data. The results show that accelerated curing provides similar or lower permeability results.

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)0.000
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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.125
GPT teacher head0.382
Teacher spread0.257 · 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
Published2023
Admission routes1
Has abstractyes

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Same venueTSpace→Same topicConcrete and Cement Materials Research→French-language works237,207→