MétaCan
Menu
Back to cohort

Deterioration of Concrete by the Oxidation of Sulphide Minerals in the Aggregate

2013· article· en· W1189654915 on OpenAlexaffabout
Josée Duchesne, Benoît Fournier

Bibliographic record

VenueJournal of Civil Engineering and Architecture · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicMine drainage and remediation techniques
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsAggregate (composite)MetallurgyEnvironmental scienceMaterials scienceComposite material

Abstract

fetched live from OpenAlex

Cases of degradation of concrete associated to iron sulphides in aggregates were recently recognized in the Trois-Rivieres area, Canada. The aggregate used to produce concrete was an anorthositic gabbro containing various proportions of pyrite, pyrrhotite, chalcopyrite and pentlandite. Quantitative microanalysis on sulphide minerals show that pyrrhotite contains small amount of Ni, Co, Cu and As substituting for Fe in the mineral structure. Considering element substitution, x value in the chemical formula (Fe1-xS) was calculated to 0.099 in the pyrrhotite studied. Petrographic examination of damaged concretes showed the presence of oxidized pyrrhotite. The observation of polished samples shows, in several cases, that the pyrite is intact while the pyrrhotite presents evident signs of oxidation. In the presence of water and oxygen, pyrrhotite oxidizes to form iron oxyhydroxides and sulphuric acid. The acid then reacts with the phases of the cement paste and provokes the formation of gypsum and ettringite. These minerals were observed by SEM-EDS (scanning electron microscope/energy dispersive x-ray spectrometer) and their precipitation causes a volume increase that creates expansion and cracking of the concrete.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.053
Threshold uncertainty score0.094

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.003
GPT teacher head0.184
Teacher spread0.181 · 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.

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

Citations31
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Civil Engineering and ArchitectureSame topicMine drainage and remediation techniquesFrench-language works237,207