Ultramafic Carbonated Melt‐ and Auto‐Metasomatism in Mantle Eclogites: Compositional Effects and Geophysical Consequences
Bibliographic record
Abstract
Abstract The mineralogy, chemical composition, and physical properties of cratonic mantle eclogites with oceanic crustal protoliths can be modified by secondary processes involving interaction with fluids and melts, generated in various slab lithologies upon subduction (auto‐metasomatism) or mantle metasomatism after emplacement into the cratonic lithosphere. Here we combine new and published data to isolate these signatures and evaluate their effects on the chemical and physical properties of eclogite. Mantle metasomatism involving kimberlite‐like, ultramafic carbonated melts (UM carbonated melts) is ubiquitous though not pervasive, and affected between ~20% and 40% of the eclogite population at the various localities investigated here, predominantly at ~60–150 km depth, overlapping cratonic midlithospheric seismic discontinuities. Its hallmarks include lower jadeite component in clinopyroxene and grossular component in garnet, an increase in bulk‐rock MgO ± SiO2, and decrease in FeO and Al2O3 contents, and LREE‐enrichment accompanied by higher Sr, Pb, Th, U, and in part Zr and Nb, as well as lower Li, Cu ± Zn. This is mediated by addition of a high‐temperature pyroxene from a UM carbonated melt, followed by redistribution of this component into garnet and clinopyroxene. As clinopyroxene‐garnet trace‐element distribution coefficients increase with decreasing garnet grossular component, clinopyroxene is the main carrier of the metasomatic signatures. UM carbonated melt‐metasomatism at >130–150 km has destroyed the diamond inventory at some localities. These mineralogical and chemical changes contribute to low densities, with implications for eclogite gravitational stability, but negligible changes in shear‐wave velocities, and, if accompanied by H2O‐enrichment, will enhance electrical conductivities compared to unenriched eclogites.
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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 | 0.000 |
| 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".