Multicomponent diffusion in aluminosilicate garnet: coupling effects due to charge compensation
Bibliographic record
Abstract
Three kinds of multicomponent diffusion effects, arising from three distinct physical mechanisms, are evident in stranded diffusion profiles at the rims of partially resorbed garnets from the contact aureole of the Makhavinekh Lake Pluton, northern Labrador. Profiles that display a subtle maximum in Ca concentration are explained by the prevailing ideal mean-field theory of multicomponent diffusion, but models implementing that theory cannot replicate inverted profiles for Li and internal maxima for Nd, Sm, and Eu. The anomalous profiles are quantitatively reproduced, however, by numerical simulations employing a model based on coupled movement of charge-compensating groups during diffusional transport of yttrium and the rare-earth elements (Y+REEs). An alkali-type charge-compensation mechanism for the heterovalent substitution of Y+REEs on dodecahedral sites in garnet produces direct charge coupling between Li+ and (Y+REE)3+ and leads to co-diffusion of Li+-(Y+REE)3+ pairs, with the result that Li profiles closely mimic those for Y+REEs. A menzerite-type charge-compensation mechanism produces indirect charge coupling among all Y+REE components, with the result that the fluxes of low-abundance REEs become partly dependent on the fluxes of Y+REEs present in higher abundance. These findings have implications for the robustness of Li profiles in garnet as monitors of fluid–rock interaction, for geochronology based on the Sm–Nd and Lu–Hf systems, and for future experimental attempts to quantify rates of diffusion in garnet.
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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 | 0.000 | 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".