Halogen heterogeneity in the subcontinental lithospheric mantle revealed by I/Br ratios in kimberlites and their mantle xenoliths from South Africa, Greenland, China, Siberia, Canada, and Brazil
Bibliographic record
Abstract
Abstract To investigate halogen heterogeneity in the subcontinental lithospheric mantle (SCLM), we measured the concentrations of Cl, Br, and I in kimberlites and their mantle xenoliths from South Africa, Greenland, China, Siberia, Canada, and Brazil. The samples can be classified into two groups based on halogen ratios: a high-I/Br group (South Africa, Greenland, Brazil, and Canada) and a low-I/Br group (China and Siberia). The halogen compositions were examined with the indices of crustal contamination using Sr and Nd isotopes and incompatible trace elements. The results indicate that the difference between the two groups was not due to different degrees of crustal contamination but from the contributions of different mantle sources. The low-I/Br group has a similar halogen composition to seawater-influenced materials such as fluids in altered oceanic basalts and eclogites and fluids associated with halite precipitation from seawater. We conclude that the halogens of the high-I/Br group are most likely derived from a SCLM source metasomatized by a fluid derived from subducted serpentinite, whereas those of the low-I/Br group are derived from a SCLM source metasomatized by a fluid derived from seawater-altered oceanic crust. The SCLM beneath Siberia and China could be an important reservoir of subducted, seawater-derived halogens, while such role of SCLM beneath South Africa, Greenland, Canada, and Brazil seems limited.
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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 | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".