Variability Analysis of Compressive and Flexural Performance of Coconut Fibre Reinforced Self-Compacting Concrete
Bibliographic record
Abstract
Self-compacting concrete (SCC) is a high-performance material that flows freely and consolidates without segregation or bleeding. This study investigated the effectiveness of incorporating coconut fiber into SCC to improve its strength and toughness. Three mixtures with coconut fiber inclusions of 0.2%, 0.4%, and 0.6% by weight of cement were used. The addition of coconut fiber reduced the workability and passing ability of the concrete, but all mixes met the SCC specification. The CFRSCC with 0.2% had the highest compressive and flexural strengths. The study concluded that adding 0.2% coconut fiber to SCC can increase its strength. The use of natural fibers like coconut can enhance the properties of concrete and could be an alternative to synthetic fibers, especially in regions where natural fibers are locally available and cost-effective.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".