Sr-Nd-Pb isotopes of fluids in diamond record two-stage modification of the continental lithosphere
Bibliographic record
Abstract
High-density fluid (HDF) microinclusions in diamonds allow direct investigation of deep carbon-and water-rich fluids that influence the properties of Earth's mantle.Identifying the sources and evolution of such fluids in the context of different potential mantle reservoirs is difficult due to the limited radiogenic isotope data.Here, we report Sr-Nd-Pb isotope compositions of silicic to low-Mg carbonatitic HDFs in a suite of diamonds from a single source in Canada.Relationships between isotopes and trace element compositions indicate the contribution of two distinct sources within the continental lithosphere: one with relatively primitive isotopic compositions characterised by εNd of -0.2, 87 Sr/ 86 Sr of 0.7044 and 206 Pb/ 204 Pb of 17.52, and another with more unradiogenic εNd < -16 and radiogenic 87 Sr/ 86 Sr and 206 Pb/ 204 Pb > 0.713 and 18.3, respectively.We suggest that the latter reflects an old metasomatic event in the continental lithosphere involving fluid addition from a subducting slab, most probably in the Paleoproterozoic.HDFs formed and their host diamonds crystallised in a more recent metasomatic event, indicated by the unaggregated nitrogen of the diamonds, where fluids from both sources mixed.HDFs from Canada, Botswana, and Congo have comparable isotope-trace element relationships, suggesting contributions of similar sources in distinct lithospheric provinces worldwide.
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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 | 0.000 | 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) | 0.001 | 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".