Partition of Platinum, Palladium, Iridium, and Gold among Coexisting Minerals from the Deep Ore Zone, Strathcona
Bibliographic record
Abstract
Platinum, palladium, iridium, and gold were determined by radiochemical neutron activation analysis in coexisting pyrrhotite, pentlandire, chalcopyrite, and magnetite from the deep ore zone of Strathcona mine, Sudbury, Ontario. Platinum and palladium are the most abundant noble metals and their average concentrations reach ppm levels in chalcopyrite and pentlandite, whereas average gold and iridium values do not exceed 15 ppb, except for the gold content of pentlandite which averages 118 ppb. Individual noble metals are strongly associated with specific sulfide minerals. Palladium and gold are concentrated with pentlandite, and platinum and iridium are associated with chalcopyrite. Relative to the most abundant sulfide, pyrrhotite, palladium and gold are concentrated in pentlandite by a factor of approximately 14, and platinum and iridium are concentrated in chalcopyrite by a factor of approximately 6. Except for iridium, mag-netite is depleted in noble metals relative to all sulfide minerals. Using phase relations in the Cu-Fe-Ni-S system as a guide to the paragenesis of the principal sulfide minerals, 4t is suggested that the palladium-pentlandite association is best explained by a solid solution of much of the palladium in pyrrhotite at magmatic tem-peratures with a subsequent exsolution with pentlandite below 300øC. The same process was presumably significant in controlling the gold distribution. Some chalcopyrite probably exsolved from the pyrrhotite solid soluton at sub-solidus temperatures, but the direct precipitation.of chalcopyrite from a copper-rich magmatic liquid is also feasible. The platinum-chalcopyrite association therefore suggests that the platinum distribution is controlled in part by a solid solution in pyrrhotite and in part by fractionation into a copper-rich magmatic liquid. The distribution of platinum values in this Strathcona deep ore zone suite indicates that both processes were operative.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 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".