PALLADIUM, A PROGRAM TO MODEL THE CHROMATOGRAPHIC SEPARATION OF THE PLATINUM-GROUP ELEMENTS, BASE METALS AND SULFUR IN A SOLIDIFYING PILE OF IGNEOUS CRYSTALS
Bibliographic record
Abstract
The formation of platinum-group-element (PGE) deposits in layered intrusions involves an interplay of sulfide saturation and modifications that might be caused by migrating silicate liquid and volatile fluid. The program PALLADIUM has been written to illustrate the chromatographic effects occurring in a pile of igneous crystals + liquid in a fractionating magmatic system, with a pile of cumulates that is both growing in thickness while also undergoing compaction, solidification and possible separation and migration of a volatile fluid phase. The program links compaction-driven mass transport with conductive cooling and compositional evolution controlled by equilibrium partitioning between phases. The elements S, Pd, Ir, Cu and Ni are assumed to follow simple partitioning behavior among the potential phases that include immiscible sulfide liquid, silicate liquid, volatile fluid, and Pd metal. All other precipitated solids are included in the solid matrix. The initial composition of the magma, compaction parameters and other variables can be set by the user. Two examples involving the crystallization of a “dry” and a “wet” magma are presented to illustrate the utility of the program. Both cases illustrate how chromatographic and reaction effects can lead to chromatographic separation of the elements and the formation of metal alloys and other PGE-rich, S-poor phases beneath sulfide zones, as are observed in many PGE deposits. The principal difference between the “dry” magmatic precipitation of sulfide as a cotectic phase and those sulfides arising from fluid migration in a crystallizing “wet” pile of crystals is that the former cannot exceed cotectic proportions of sulfide unless there is preferential settling of sulfide, and the Pd metal zone is ephemeral. In contrast, the latter mechanism can produce sulfide-enriched zones in which sulfide abundance exceeds expected cotectic levels of saturation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".