MétaCan
Menu
Back to cohort

Sulfate Attack on Concrete: Effect of Partial Immersion

2010· article· en· W2082102342 on OpenAlexaff
Julie Ann Hartell, Andrew J. Boyd, Christopher C. Ferraro

Bibliographic record

VenueJournal of Materials in Civil Engineering · 2010
Typearticle
Languageen
FieldEngineering
TopicConcrete Corrosion and Durability
Canadian institutionsMcGill University
Fundersnot available
KeywordsSulfateSodium sulfateUltimate tensile strengthImmersion (mathematics)Materials scienceCompressive strengthComposite materialCylinderEfflorescenceTensile testingSodiumForensic engineeringEngineeringMetallurgyMathematicsMechanical engineering

Abstract

fetched live from OpenAlex

Traditionally, the extent of sulfate attack is qualified through visual rating or quantified by the percent expansion of slender bars completely submerged in sulfate solution. There are currently no standardized test methods that take into account the change in engineering properties because of deleterious mechanisms. Moreover, the exposure regime used to evaluate sulfate attack, complete immersion, is not typically representative of that encountered in the field. For these reasons, the objective of the research presented herein is to quantify the degree of sodium sulfate attack through the degradation of mechanical properties, specifically the compressive and splitting tensile load capacities of standard cylindrical specimens. A novel exposure regime is utilized wherein the specimens are only partially submerged in 5% sodium sulfate solution, creating an evaporation front similar to that of field exposure. It was found that the portion submerged in sulfate solution, although visually pristine, was the weaker portion of the cylinder for both mechanical tests, even though the other half showed extensive signs of surface disintegration caused by salt crystallization.

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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
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)0.0010.000

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 head0.009
GPT teacher head0.236
Teacher spread0.227 · 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

Citations39
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Materials in Civil EngineeringSame topicConcrete Corrosion and DurabilityFrench-language works237,207