Efficacy of forest based ash as a supplementary cementing material for concrete
Bibliographic record
Abstract
This paper presents a feasibility study on the effects of forest based ash (FBA) on the mechanical performance of concrete. Four such samples were obtained from the pulp and paper industry as the residual byproduct of their hog fuel. They were analyzed for grain size distribution, density, morphology, and oxide content. Subsequently, the ash was employed as a cement substitute (up to 20% by mass) and the resulting concrete was examined for mechanical properties. Results show that all four FBA samples were coarser than Portland cement with mean particle size around 100–1000 microns. Further, X-ray fluorescence showed that the FBA samples were predominantly composed of CaO, with significant amounts of SO3 and alkali oxides at levels that exceed maximum limits allowed for the latter by ASTM. This poses concerns on durability. Nevertheless, based on short-term compressive and tensile performance alone, this study shows that FBA could replace up to 15% by mass of cement.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".