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Record W4280569712 · doi:10.1680/jmacr.22.00061

Reliability of the damage rating index to assess the condition of concrete affected by external sulfate attack

2022· article· en· W4280569712 on OpenAlexaff
Andisheh Zahedi, Leen Saliba, Leandro Sanchez, Andrew J. Boyd

Bibliographic record

VenueMagazine of Concrete Research · 2022
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsMcGill UniversityUniversity of Ottawa
Fundersnot available
KeywordsSulfateSodium sulfateReliability (semiconductor)SodiumEnvironmental scienceCementChlorideSalt (chemistry)Materials scienceGeotechnical engineeringComposite materialChemistryGeologyMetallurgy

Abstract

fetched live from OpenAlex

The damage rating index (DRI) has proven to be a quite reliable microscopic technique enabling the condition assessment of concrete affected by internal swelling reactions. Yet, very little research has been conducted on the use of the DRI to appraise induced deterioration caused by physical salt attack (PSA) and external sulfate attack (ESA). This study aims to assess the condition of concrete subjected to different salt solutions (i.e. sodium sulfate (Na 2 SO 4 ), sodium chloride (NaCl), seawater and limewater), and exposure conditions (i.e. partially and fully immersed) through the DRI. Concrete specimens displaying two distinct water/cement ratios (i.e. 0.45 and 0.65) were manufactured and exposed to the above salt solutions for 12 months. Then, the samples were removed from the exposure conditions and prepared for microscopic analysis. The DRI was shown to be an effective technique to assess the condition of PSA- and ESA-affected concrete since different degrees of damage and features were captured for the various exposure conditions studied.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.045
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.044
GPT teacher head0.338
Teacher spread0.293 · 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

Citations5
Published2022
Admission routes1
Has abstractyes

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