Evaluation of Potential Factors Affecting Steel Slag Carbonation
Bibliographic record
Abstract
Steel slag is a solid waste product generated during the carbonation stage of steelmaking. It has high levels of heavy metals and substantial amounts of free calcium and magnesium oxide, making it unsuitable for use as a cement material. Furthermore, the disposal of steel slag in landfills requires many resources and can seriously contaminate the surrounding environment. One method of reducing its negative environmental impact is carbonation, which involves reacting steel slag with carbon dioxide to form stable minerals. However, many parameters influence the carbonation efficiency of steelmaking slag, including temperature, time, particle size, pressure, CO2 concentration, liquid-to-solid ratio, moisture content, humidity, additives, etc. To this end, this paper comprehensively reviews the most important steel slag carbonation-influencing factors. Moreover, it compares the characteristics from two perspectives based on their causes and effects on carbonation. Finally, this article reviews earlier studies to identify the factors that affect steel slag carbonation and the potential of carbonated steel slag as a sustainable construction material. Based on previous research, it systematically examines all the elements for future work that need to be improved.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".