MétaCan
Menu
Back to cohort
Record W4308989633 · doi:10.1016/j.dibe.2022.100098

Improvement of treated spent pot lining reactivity in cementitious material by calcination

2022· article· en· W4308989633 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueDevelopments in the Built Environment · 2022
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsUniversité LavalÉcole de Technologie Supérieure
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCalcinationPozzolanCementitiousReactivity (psychology)CementFly ashMaterials scienceInertLeaching (pedology)Compressive strengthPozzolanic reactionPhosphogypsumPortland cementPozzolanic activityMetallurgyMineralogyChemical engineeringChemistryComposite materialGeologyOrganic chemistryRaw materialSoil water

Abstract

fetched live from OpenAlex

Treating spent pot lining by the Low Caustic Leaching and Liming (LCLL) process creates an inert non-hazardous residue called LCLL Ash. Ground as a fine powder and calcined, LCLL Ash showed a pozzolanic behavior in cement. The effect of the calcination temperatures on LCLL Ash reactivity was studied by compressive strength activity index, Frattini tests, and RILEM R3 tests, followed by XRD analysis. When calcinating LCLL Ash at temperatures below 800 °C, no differences in reactivity were seen between calcined and non-calcined LCLL Ash. At 800 °C, the formation of nepheline caused an alkalis uptake, showing a slightly lower reactivity of LCLL Ash than cement at 112 days. Beyond 800 °C up to 1200 °C, calcined LCLL Ash manifested better amorphization of phases and increased reactivity, similar to cement at 112 days. Finally, neither delay on hydration nor hydroreactivity was observed with calcined LCLL Ash starting at 800 °C.

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.

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 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 score0.074
Threshold uncertainty score1.000

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 head0.013
GPT teacher head0.226
Teacher spread0.213 · 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