An automated method for the calculation of <i>P–T</i> paths from garnet zoning, with application to metapelitic schist from the Kootenay Arc, British Columbia, Canada
Bibliographic record
Abstract
Abstract An automated method for the calculation of P–T paths based on garnet zoning is presented and used to interpret zoning in metapelitic schist from the southern Canadian Cordillera. The approach adopted to reconstruct the P–T path is to match garnet compositions along a radial transect with predictions from thermodynamic forward models, while iteratively modifying the composition to account for fractional crystallization. The method is applied to a representative sample of garnet‐ and staurolite‐bearing schist from an amphibolite facies Barrovian belt in the southern Canadian Omineca belt. Garnet zoning in these schists is concentric and largely continuous from core to rim. Three zones are present, the first two of which coincide with sector‐zoned cores of garnet crystals. Similar zoning is developed in rocks that contain or lack staurolite, respectively, suggesting garnet growth was restricted to the initial part of the prograde P–T path prior to the development of staurolite. Growth zoning in large garnet crystals has not been significantly modified by diffusion. This interpretation is based on zoning characteristics of garnet crystals and is further supported by results of a forward model incorporating the effects of simultaneous fractional crystallization and intracrystalline diffusion. The P–T path calculated for this rock includes an initial, linear stage with a high dP/dT, and a later stage dominated by heating. The approach adopted in this study may have application to other garnet‐bearing rocks in which growth zoning is preserved.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".