Constraining the conditions of Barrovian metamorphism in Sikkim, India: <i>P</i>–<i>T</i>–<i>t</i> paths of garnet crystallization in the Lesser Himalayan Belt
Bibliographic record
Abstract
Abstract Garnet crystallization in metapelites from the Barrovian garnet and staurolite zones of the Lesser Himalayan Belt in Sikkim is modelled utilizing Gibbs free energy minimization, multi‐component diffusion theory and a simple nucleation and growth algorithm. The predicted mineral assemblages and garnet‐growth zoning match observations remarkably well for relatively tight, clockwise metamorphic P–T paths that are characterized by prograde gradients of ∼30 °C kbar−1 for garnet‐zone rocks and ∼20 °C kbar−1 for rocks from the staurolite zone. Estimates for peak metamorphic temperature increase up‐structure toward the Main Central Thrust. According to our calculations, garnet stopped growing at peak pressures, and protracted heating after peak pressure was absent or insignificant. Almost identical P–T paths for the samples studied and the metamorphic continuity of the Lesser Himalayan Belt support thermo‐mechanical models that favour tectonic inversion of a coherent package of Barrovian metamorphic rocks. Time‐scales associated with the metamorphism were too short for chemical diffusion to substantially modify garnet‐growth zoning in rocks from the garnet and staurolite zones. In general, the pressure of initial garnet growth decreases, and the temperature required for initial garnet growth was reached earlier, for rocks buried closer toward the MCT. Deviations from this overall trend can be explained by variations in bulk‐rock chemistry.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 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".