MétaCan
Menu
Back to cohort
Record W4231957757 · doi:10.32920/ryerson.14652384.v1

The Use Of Wollastonite to Enhance Fresh and Mechanical Properties of Concrete

2021· preprint· en· W4231957757 on OpenAlexfundno aff
Hyder Jahim

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicInnovations in Concrete and Construction Materials
Canadian institutionsnot available
FundersQueen's University
KeywordsWollastoniteCompressive strengthMaterials scienceCementMortarComposite materialPozzolanSlumpFiller (materials)Consolidation (business)Portland cementChemistry

Abstract

fetched live from OpenAlex

Wollastonite is a natural material that consists of calcium silica oxides. This research program focused on evaluating the feasibility of using wollastonite in concrete or mortar. The experimental program for this study is designed to investigate the strength conribution for mortar cubes with wollastonite at 5 and 10% replacement of sand or Porland Cement (PC). The compressive strength has shown remarkable improvment in all ages compared with control mix when there was 5% sand replacement. The study also tested the compresiive strenght for concrete with the same levelsof wolllastonite as in mortar. The compressive strength fo cyclinders having 5% and 10% wollastonite powder as cement replacement was not improved compared with the control mix. Furthermore, the study tested the possibility of using wollastonite as mineral filler in Self Consolidation Concrete (SCC). Mixture of SCC were designed with the levels 0, 8, 10% of wollastonite powder. The fresh properties were evaluated using the slump flow.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.033
GPT teacher head0.241
Teacher spread0.208 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2021
Admission routes1
Has abstractyes

Explore more

Same topicInnovations in Concrete and Construction MaterialsFrench-language works237,207