Valorization of Cement Kiln Dust (CKD) from the Ain-Al-Kebira Cement Plant (Algeria) in Building Materials
Bibliographic record
Abstract
Solid waste management is one of the world's major environmental concerns.Cement Kiln Dust (CKD) is a by-product of cement manufacturing.It is a fine-grained, solid and highly alkaline particulate material.Environmental concerns related to Portland cement production, CO2 emissions and CKD disposal are becoming increasingly important.Replacing some of the cement with CKDs will significantly reduce the amount of clinker to be produced, which will then reduce CO2 emissions into the atmosphere and transform the CKDs into useful products while allowing sustainable concrete/mortar to be produced in an environmentally friendly way.This work is part of the recovery of machining waste from the manufacture of cements produced from a local Algerian cement plant, in particular CKD.Study of the use of CKD influence in mortar and concrete reveals that the percentage increase in CKD accelerates setting time.From the obtained results (simple compression and bending tension) we can conclude that the use of CKD in mortar can be favorable for substitution and/or addition up to 10%.
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 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".