Comportement physico-chimique de mélanges à base de poussières de four de cimenterie et de cendres volantes
Bibliographic record
Abstract
Enhancing the value of the cement kiln dust so as to use it as an environmental barrier requires, amongst other things, the addition of fly ashes in order to improve the different properties needed to insure a better placing and a long term efficiency. Taking advantage of different experimental techniques, particular attention was devoted to the physicochemical behaviour of different kiln dusts associated with the fly ashes. Depending on the nature of the added compound, a different behaviour may condition the evolution of the mixtures with an effect on their stability. Indeed, this study has confirmed the improvement of the physicochemical properties of the dusts interacting with the fly ashes rich in silica and poor in lime, which argues well for their use as an environmental barrier. Moreover, the follow up has led to a better understanding of certain mechanisms generated by the systems dealt with. Hence, after hydration and different chemical transformations, some expansive phases as the ettringite, gypsum, syngenite, and portlandite develop in the paste, and therefore condition the behaviour of the mixtures worked out.Key words: cement kiln dusts, fly ashes, stabilization, physicochemistry, environmental barrier, lixiviation.[Journal translation]
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".