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Record W4365512508 · doi:10.1016/j.cement.2023.100070

Effect of fluorite addition on the reactivity of a calcined treated spent pot lining in cementitious materials

2023· article· en· W4365512508 on OpenAlexaff
Victor Brial, Hang Tran, Luca Sorelli, David Conciatori, Claudiane Ouellet‐Plamondon

Bibliographic record

VenueCement · 2023
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsUniversité LavalÉcole de Technologie Supérieure
Fundersnot available
KeywordsFluoriteCementitiousCalcinationReactivity (psychology)Materials scienceCementChemistryMetallurgyMedicineOrganic chemistry

Abstract

fetched live from OpenAlex

Treating SPL by the low caustic leaching and liming process generates an inert nonhazardous residue called LCLL Ash and a fluorite byproduct Calcined LCLL Ash that is ground into a fine powder demonstrates pozzolanic behavior in cement. The effect of the calcination temperature and fluorite byproduct addition on the reactivity of LCLL Ash was studied by the compressive strength activity index, Frattini test and Rilem R 3 tests followed by XRD analysis. At 800°C, the formation of nepheline causes alkali uptake, the LCLL Ash showed a slightly lower reactivity with 10% fluorite addition. At 1000°C, calcined LCLL Ash/CF showed a better amorphization of phases and increasing reactivity due to reactions between fluorite and sodium oxide. Unlike LCLL Ash, no delay in hydration or hydro reactivity was observed with calcined LCLL Ash/CF.

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)0.001
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 score0.003
Threshold uncertainty score0.968

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.022
GPT teacher head0.277
Teacher spread0.255 · 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

Citations4
Published2023
Admission routes1
Has abstractyes

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