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Optimization of Drilling Cuttings Reactivity as a Supplementary Cementitious Material in Ternary Cements

2023· article· en· W4388568699 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.

Bibliographic record

VenueMaterials Research · 2023
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsDiscovery Air (Canada)
FundersFundação de Amparo à Pesquisa do Estado da BahiaConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsPortland cementMaterials scienceCementitiousCompressive strengthCementComposite materialTernary operation

Abstract

fetched live from OpenAlex

This study evaluates the influence of milling on the reactivity of drilling cuttings (DC) utilized as supplementary cementitious material in ternary cements (TC). The drilling cuttings milling study varied the time (2, 5, 10, 15, and 20 min) and rotation speed (200 and 300 rpm), determining the specific milling energy and grindability index. The hydration of TC pastes containing DC with different particle size distributions was evaluated by isothermal calorimetry during the first 72 hours, XRD/Rietveld at 3 and 28 days, compressive strength and absorption. The incorporation of milled DC improved the TC hydration kinetics compared to reference pastes of ordinary Portland cement (REF.PC). After 28 days, the TC pastes with the D50% diameter smaller than 11 µm reached at least 70% of the resistance to the strength of the Portland cement paste. Milled DC contributes to the physical and nucleation effect of the TC pastes studied and can be used as an SCM.

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)0.003
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 score0.012
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0120.000

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 head0.045
GPT teacher head0.339
Teacher spread0.294 · 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