Analysing the segregation of coarse tailings particles with a zone-formation differential settling model
Bibliographic record
Abstract
This study delves into the segregation and settling behaviours of tailings suspensions with varying initial solids contents, with a specific focus on the initial segregation process. Conventional and interruptive batch settling tests were performed to evaluate the hindered settling process of copper tailings. During these tests, particular attention was paid to the differential settling behaviour at the initial stage, during which coarse particles segregated from the suspension and accumulated at the bottom. The particle size distribution profile of the suspension was analysed in detail, revealing that segregation was a prevalent phenomenon in all settling tests. To perform a theoretical analysis of this segregation behaviour, a zone-formation differential settling model was introduced and applied, allowing a detailed discussion of the settling behaviour of individual particle species. Consequently, the findings offer insights into the variation of the segregation behaviour and formation of the sediment under different initial conditions. Suggestions are also provided for the application of the zone-differential settling model on the sedimentation of tailings which contains fine particle species.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".