Insights into garnet growth in S-type granite from Lu–Hf dating and trace element mapping
Bibliographic record
Abstract
Abstract Garnet is a common minor phase in S-type granites and pegmatites, but its petrogenesis remains poorly constrained. Garnet in these systems may have crystallized from the melt or it may represent inherited grains derived from the source or xenocrysts from the wall rocks. Although garnet has the potential to provide unique insights into the magmatic evolution and crystallization intervals of S-type granites and pegmatites, its geochemical and chronological record is underexplored. In this study, we investigate the Lu–Hf age and trace-element record of garnet in the Neoarchean Decelles Batholith (c. 2670–2620 Ma), southeastern Superior Craton, Canada. The batholith comprises one of the most voluminous granites in the region and was likely sourced from anatexis of the metasedimentary Pontiac Group at depth. Garnet Lu–Hf geochronology yielded ages between 2667.5 ± 3.9 and 2656.0 ± 7.1 Ma, overlapping with U–Pb monazite ages from the batholith and Lu–Hf ages from the host rocks. LA-ICP-MS trace-element mapping revealed well-preserved sharp oscillatory—locally sector—zoning in Li, P, Sc, Ti, Y, Zr, REE, Hf, Th, and U, contrasting with weak major element zoning. Garnet grains exhibit a core with concentric zoning and an overgrowth domain truncating core patterns, reflecting both trace-element uptake controlled by varying crystal growth rates, element supply and diffusion at the garnet-matrix interface in the presence of melt, and cation supply limitations due to co-crystallization of muscovite, monazite, apatite, and zircon. The data support a magmatic origin for garnet in the peraluminous granite and demonstrate that the oscillatory zoning can be diagnostic. Moreover, the new Lu–Hf garnet dates place new constraints on the timing of crystallization of the Decelles Batholith. This study provides new insights into the conditions of garnet crystallization in granitic systems and illustrates the versatility of garnet in constraining the onset and later evolution of peraluminous granitoid magmatism. Ultimately, our study underscores the necessity of case-by-case assessment of garnet origins in S-type granites, emphasizing trace-element mapping as a key tool for petrogenetic interpretation.
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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 | 0.001 |
| Science and technology studies | 0.000 | 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".