Dependence of reaction kinetics on H<sub>2</sub>O activity as inferred from rates of intergranular diffusion of aluminium
Bibliographic record
Abstract
Abstract Quantitative constraints on the accelerative effects of H2O on the kinetics of metamorphic reactions arise from a comparison of rates of intergranular diffusion of Al in natural systems that are fluid‐saturated, hydrous but fluid‐undersaturated, and nearly anhydrous. Widths of symplectitic reaction coronas around partially resorbed garnet crystals in the contact aureole of the Makhavinekh Lake Pluton, northern Labrador, combined with time–temperature histories from conductive thermal models, yield intergranular diffusivities for Al from ∼700–900 °C under nearly anhydrous conditions. Those rates, when extrapolated down temperature, are approximately three orders of magnitude slower than rates derived from re‐analysis of garnet resorption coronas formed under hydrous but fluid‐undersaturated conditions near 575 °C in rocks of the Llano Uplift of central Texas, which are in turn approximately four orders of magnitude slower than rates at comparable temperatures derived from numerical simulations of prograde garnet growth in fluid‐saturated conditions in rocks from the Picuris Range of north‐central New Mexico. Thus, even at constant temperature, rates of intergranular diffusion of Al – and corresponding length scales and timescales of metamorphic reaction and equilibration – may vary by as much as seven orders of magnitude across the range of H2O activities found in nature.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".