Up, down, or sideways: emplacement of magmatic Fe–Ni–Cu–PGE sulfide melts in large igneous provinces
Bibliographic record
Abstract
The preferential localization of Fe–Ni–Cu–PGE sulfides within the horizontal components of dike–sill–lava flow complexes in large igneous provinces (LIPs) indicates that they were fluid dynamic traps for sulfide melts. Many authors have interpreted them to have collected sulfide droplets transported upwards, often from deeper “staging chambers”. Although fine (<1–2 cm) dilute (<10%–15%) suspensions of dense (∼4–5 g/cm3) sulfide melt can be transported in ascending magmas, there are several problems with upward-transport models for almost all LIP-related deposits: (1) S isotopic data are consistent with nearby crustal sources, (2) xenoliths appear to be derived from nearby rather than deeper crustal sources, (3) lateral sheet flow or sill facies of major deposits contain few if any sulfides, (4) except where there is evidence for a local S source, sulfides or chalcophile element enrichments rarely if ever occur in the volcanic components even where there is mineralization in the subvolcanic plumbing system, and (5) some lavas are mildly to strongly depleted in PGE >>> Cu > Ni > Co, indicating that unerupted sulfides sequestered PGEs at depth. Two potential solutions to this paradox are that (i) natural systems contained surfactants that lowered sulfide–silicate interfacial tensions, permitting sulfide melts to coalesce and settle more easily than predicted from theoretical/experimental studies of artificial/analog systems, and (or) (ii) sulfides existed not as uniformly dispersed droplets, as normally assumed, but as fluid-dynamically coherent pseudoslugs or pseudolayers that were large and dense enough that they could not be transported upwards. Regardless of the ultimate explanation, it seems likely that most high-grade Ni–Cu–PGE sulfide deposits in LIPs formed at or above the same stratigraphic levels as they are found.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".