Thermodynamic and Kinetic Controls on the Growth of Metapelitic Garnet in the Danba Dome (SW China): Insights From Microstructure, Element Mapping and Thermodynamic Modelling
Bibliographic record
Abstract
ABSTRACT Understanding the growth history of metamorphic garnet is crucial for revealing metamorphic evolution and distinguishing thermodynamic and kinetic contributions during metamorphism. Garnet crystals in metapelites from a Barrovian‐type metamorphic sequence in the Danba dome (SW China) record microstructural and compositional patterns that provide insights into the petrogenetic evolution of the samples during metamorphism. While sector‐zoned garnet in graphite‐rich layers and garnet crystals with trace element and microstructural evidence of biotite overgrowth are common in the lower grade garnet–staurolite–kyanite zones, these features are absent in the higher grade sillimanite zone. Reactions associated with accessory phases during garnet growth may explain the yttrium (Y) and heavy rare earth element (HREE) annuli observed in garnet of rocks from the garnet and staurolite zones. The absence of these Y and HREE annuli in garnet of rocks from the sillimanite zone is explained by variations in the bulk‐rock composition of the samples, which resulted in different pressure–temperature ( P–T ) conditions of garnet‐forming and accessory phase breakdown reactions (e.g., monazite–allanite transition). Whereas isopleth thermobarometry applied to the cores of the largest garnet crystals demonstrates initial garnet growth close to equilibrium in a rock that was collected very close to the garnet isograd, different degrees of driving force (~1.2 – 2.3 kJ per mole 12‐oxygen garnet) were required for garnet nucleation in other rocks, pointing to varying reaction affinities for initial garnet growth. Garnet crystallization modelling for a rock from the garnet zone also predicts the observed mineral assemblages and garnet growth zoning exceptionally well and yields peak P–T conditions that are identical to the results obtained by conventional thermobarometry. Taken together, these results imply that the growth of metapelitic garnet in the Danba dome was controlled by both thermodynamic (e.g., P–T composition ( X ) relations) and kinetic (e.g., elemental mobility, protolith heterogeneity, reaction history, and chemical driving force for garnet nucleation) factors. This study underscores the specific impacts of these factors on the growth characteristics of metapelitic garnet in a regional metamorphic context.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".