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Record W3016660056 · doi:10.18552/2019/idscmt5050

Nano-modified cementitious composites with high volume supplementary cementitious materials incorporating basalt fiber pellets

2019· article· en· W3016660056 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

VenueSustainable construction materials and technologies · 2019
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsUniversity of WinnipegUniversity of Manitoba
Fundersnot available
KeywordsMaterials sciencePelletsComposite materialCementitiousNano-Basalt fiberFiberVolume (thermodynamics)Cement

Abstract

fetched live from OpenAlex

In this study, high performance nano-modified cementitious composites were developed. These composites incorporate 50% fly ash or slag (industrial by-products) replacement of the cement component, 6% nano-silica sol and a new type of basalt fiber strands encapsulated by polymeric resins termed as basalt fiber pellets. The fresh and mechanical properties were investigated for the developed composites with different dosages of basalt pellets (2.5%, 4.5% and 6.9% by volume). Generally, the slag based composites showed improved performance compared to the fly ash based composites. Although the compressive strength of the specimens was reduced with increasing the dosage of pellets, the flexural performance of the composites was significantly enhanced in terms of post-cracking behavior, residual strength and toughness. Composites comprising 4.5% and 6.9% pellets exhibited deflectionhardening behavior. Hence, they have a promising potential for many infrastructure applications.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient 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 score0.011
Threshold uncertainty score1.000

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.004
GPT teacher head0.190
Teacher spread0.186 · 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