MétaCan
Menu
Back to cohort

Advancing Basalt Fiber-fly Ash/Marble Dust Composites: A Systematic Review and Research Horizons

2025· article· en· W4415455154 on OpenAlexaboutno aff
Manmohan Meena, Vikrant Sharma, Mukul Kant Paliwal

Bibliographic record

VenueCurrent Materials Science · 2025
Typearticle
Languageen
FieldEngineering
TopicRecycling and utilization of industrial and municipal waste in materials production
Canadian institutionsnot available
Fundersnot available
KeywordsBasaltThematic mapNatural (archaeology)Fly ashThematic analysisFocus (optics)

Abstract

fetched live from OpenAlex

Introduction: Materials are crucial in the everyday existence of individuals. Nevertheless, the changing requirements of societies emphasize the necessity for the ongoing advancement of innovative materials. There has been a recent focus on composites made from natural fibers. Fly ash and marble dust can be economically beneficial alternatives to other mineral fillers. Method: This analysis included all relevant Scopus-indexed articles on the topic and was refined to a final set of 90 documents for detailed analysis. Systematic, bibliometric, co-occurrence, and thematic analyses were employed. Results: Construction and Building Materials was found to be the top journal in the discipline. China, India, Australia, and Canada were leading in terms of the number of publications. The keywords 'fly ash', 'compressive strength', and 'slags' were identified as the most prominent terms in the analyzed research studies. Discussion: This study aimed to conduct a structured, bibliometric, and thematic review of the literature on basalt fiber-fly ash/marble dust composite. The SciMAT tool facilitated the analysis of themes and concepts in the field, showcasing their evolution over time. The future research path has also been identified. Conclusion: This article has provided a detailed account of the research advancements in fly ash/marble dust-filled basalt fiber-reinforced epoxy polymer composite materials. It has clearly identified important issues and predicted future trends in the field.

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)0.017
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.032
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.035
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0320.028
Science and technology studies0.0010.001
Scholarly communication0.0030.004
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.040
GPT teacher head0.351
Teacher spread0.311 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueCurrent Materials ScienceSame topicRecycling and utilization of industrial and municipal waste in materials productionFrench-language works237,207