Water in Omphacite and Garnet From Pristine Xenolithic Eclogite: <i>T</i>‐<i>X</i>‐<i>f</i>O<sub>2</sub> Controls, Retentivity, and Implications for Electrical Conductivity and Deep H<sub>2</sub>O Recycling
Bibliographic record
Abstract
Abstract Kimberlite‐borne eclogite xenoliths having Precambrian oceanic crustal protoliths and entrained from ≥100 km depth can retain pristine geochemical features despite extended residence in the cratonic lithospheric mantle, making them valuable archives of deep chemical cycling including that of water. We determined, by Fourier Transform Infrared Spectroscopy, structural OH contents in clinopyroxene and garnet from 15 unmetasomatized eclogite xenoliths. Calculated total c(H2O) is 100–510 wt.ppm for clinopyroxene and below detection (∼2 wt.ppm) to 200 wt.ppm for garnet, while garnet δ18O, determined by Secondary Ion Mass Spectrometry, ranges from +5.0‰ to +7.3‰, (similar to high‐ and low‐temperature seawater‐altered oceanic crust). Estimated electrical conductivity in pristine eclogites increases with temperature (i.e., depth for conductive geotherms), while clinopyroxene‐garnet H2O partition coefficients decrease with increasing temperature and garnet grossular component (i.e., Ca#), similar to other incompatible components. Various considerations suggest the retention of primary H2O in the samples, likely occurring in km‐sized pods of coarse‐grained eclogite. High Al2O3 in clinopyroxene as omphacite component, stabilized during high‐pressure metamorphism, facilitates H2O uptake. Therefore, the high bulk c(H2O) estimated for samples with plagioclase‐rich, deep crustal protoliths (median 290 wt.ppm) may indicate an interaction with fluids expelled at depth from serpentinites. The c(H2O) of ancient and modern subducted bulk oceanic crust (∼220–240 wt.ppm) are similar, suggesting constant mantle ingassing since at least 3 Ga ago. This places constraints on factors, such as mantle temperatures, that determine the efficiency of deep water cycling.
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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 | 0.000 |
| 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".