Rare earth element partitioning between fluids and uraninite at 50−700 °C
Bibliographic record
Abstract
ABSTRACT Uranium deposits are globally diverse, occurring in a wide variety of geological settings and ranging in age from Archean to Holocene. As a result, understanding the mechanisms involved in the genesis and subsequent alteration of these complex deposits is challenging. Building on recent work on the geochemical signatures of uraninite, a series of experiments were designed to document the partitioning of rare earth elements between uraninite and fluids over a range of temperatures and to explore the impact of O and H diffusion, under reducing conditions, on U-Pb isotope systematics and rare earth element concentrations in uraninite. Our results show that O and H diffusion in the presence of a rare earth element-rich fluid, under reducing conditions, has no effect on rare earth element concentrations and patterns or U-Pb isotopic compositions of uraninite. Our results also show that temperature (300 to 700 °C) has no effect on the rare earth element patterns, indicating that the dominant control on rare earth element concentration in uraninite is the metal source(s), the ability of the fluids to transport rare earth elements without inducing fractionation, and the degree of recrystallization. These results have implications for nuclear forensics, as well as for our understanding of the genesis of uranium-bearing ore deposits.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".