Effects of olivine fabric, melt‐rock reaction, and hydration on the seismic properties of peridotites: Insight from the Luobusha ophiolite in the Tibetan Plateau
Bibliographic record
Abstract
Abstract In order to constrain the effects of olivine fabric, melt‐rock reaction, and hydration on the seismic properties and anisotropy of mantle rocks, we investigated serpentinized peridotites from the Luobusha ophiolite in the Indus‐Tsangpo suture of the Tibetan Plateau. A‐type and almost random olivine crystal‐preferred orientations (CPO) occur in harzburgite and dunite samples, respectively. The dunite resulted from interactions of harzburgite with boninitic melt at ~800–970°C, yielding pyroxene dissolution and olivine precipitation. The olivine neoblasts formed from the melt‐rock reaction show no evidence of dislocation creep and developed almost random CPO. Hence, the melt‐rock reaction reduced seismic anisotropy. Our results together with those from the literature indicate that A‐, B‐, C‐, D‐, and E‐type CPOs of olivine generally induceVpanisotropy patterns withVp(X) > Vp(Y) > Vp(Z),Vp(Y) > Vp(X) > Vp(Z),Vp(Z) > Vp(X) > Vp(Y),Vp(X) > Vp(Y) ≈ Vp(Z), andVp(X) > Vp(Z) > Vp(Y), respectively. The effect of serpentinization was calibrated by the comparison of seismic velocities and anisotropy measured up to 600 MPa with the values calculated from the CPO data. Although the low‐temperature (LT, <300°C) serpentinization (lizardite and chrysotile) decreasesVpby ~6–10% andVsby ~12%, it does not change the anisotropy pattern because the mesh‐texture characterized by serpentine veins perpendicular to the principal structural directions (X,Y, andZ) reduces the velocities in these orthogonal directions to almost equal extent. Thus, the magnitude of seismic anisotropy alone cannot be used as an indicator of the degree of LT serpentinization in the mantle rocks. Furthermore, Birch's law is found to hold when peridotites undergo serpentinization.
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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".