Bibliographic record
Abstract
Modeling gravity recovery of platinum group minerals (PGMs) in the grinding circuit is based on three components: Ore characterization of gravity recoverable platinum group minerals (GRPGM), their behavior in grinding mills and hydrocyclones, and the performance of the gravity recovery units. This thesis focuses on the first two components. A laboratory methodology to characterize gravity-recoverable platinum group minerals (GRPGMs) in an ore with four incremental liberation and recovery stages was developed. It was applied to quantify GRPGM content of four ore samples from Canada. To measure the behavior of GRPGMs in the grinding circuit, a methodology to characterize the already liberated (or available) GRPGMs in the circuit streams was developed. The availability of GRPGM in streams, such as ball mill discharge, was used to model the behavior of the GRPGMs in the ball mills and hydrocyclones. Combining with the potential GRPGM in an ore, they can be used for design and/or optimization of platinum group mineral recovery circuit. The GRPGM content measured by this methodology varied from 5 to 81% depending on the ore. The GRPGM size distribution varied from fine (most GRPGM below 37mum) to coarse (significant content above 212 mum). The stage size-by-size recovery and the total GRPGM content indicate that the methodology can quantify the GRPGM content of ores. Based on the measurement of the availability of GRPGM in process streams, the behavior of PGMs in ball mills and hydrocyclones is characterized in terms of the less common cumulative selection functions and conventional classification efficiency curves. Mineralogical analysis indicates that sperrylite (PtAs 2) is the dominant platinum mineral at the Clarabelle mill. Its classification efficiency is similar to that of gold, despite its lower density, while grinding rate is significantly higher than gold. The cumulative selection function of platinum and palladium is 1.3 times higher than the ore for size classes above 212 mum and 50 to 70% of the ore below 212 mum. As a result, sperrylite accumulates in finer sizes than native gold in the grinding circuit. The cumulative selection function of the platinum group minerals was calculated for the Clarabelle grinding circuit based on the survey data and the GRPGM contents in the ball mill discharge, cyclone underflow, and overflow. The methodology of characterizing the content of GRPGMs in an ore also offers a way to concentrate the minerals for mineralogical study. The use of secondary electron microscopy (SEM), variable pressure SEM and QEM*SEM for qualitative analysis of platinum group mineral mineralogy is presented and discussed. Most of the GRPGMs recovered are well liberated. Qualitative mineralogical analysis of the GRPGM and its associations in ore samples are also discussed.
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How this classification was reachedexpand
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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".