Materials Processing Strategies for Valorizing Industrial Residues in Construction: Mechanical Separation, CO2 Mineralization, and Metal Recovery/Stabilization
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Building a roadmap for integrating processing strategies for waste valorization with potential across multi-categories of industrial residues (metallurgical slags/residues, power-plant ashes, and mine wastes) is an emerging trend. This roadmap [1] seeks to address common industry questions regarding the most suitable valorization approaches for different industrial residues generated in plants based on specific conditions. The effective strategies involve specific technologies such as mechanical separation, CO2 mineralization, and metal recovery/stabilization—all of which extend the value of industrial residues before they can be largely incorporated into construction applications, supporting waste digestion and reducing direct disposal. This talk discusses route competition, research needs, and lab-industry disconnections in the roadmap, and presents two main cases: copper mine tailings and Waste-to-Energy (WTE) residues.
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.
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 | 0.000 | 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 | 0.001 |
| 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 it