An empirically derived kinetic model for albitization of detrital plagioclase
Bibliographic record
Abstract
We propose an empirically derived model that estimates the extent of reaction for albitization of plagioclase as a function of time, grain surface area, and temperature from 0 to 200°C. We use a kinetic formulation independent of pressure, and consistent with the Rate Law, which quantifies the dependence of the reaction rate on the initial concentration of the reacting material, and the Arrhenius equation. The formulation is described by the function: \\\[{-}\\frac{d{\[}An{\]}}{dt}{=}S\_{m}k{\[}An\_{o}{\]}\^{2}(1{-}{\\bar{{\\Omega}}})\\\] where *d*\[*An*\]/*dt* is the rate change of the anorthite mole fraction with time, *S*~*m*~ the mineral surface area (cm^2^), *k* the rate constant 1/cm^2^ s, \[*An*~*o*~\] is a constant representing the initial anorthite mole fraction, and Ω̄ a constant weighed average saturation index. We derive the apparent activation energy (*E*~*a*~) and frequency factor (*A*), both present in the rate constant *k*, by fitting them to the extent of albitization measured in 11 samples from the San Joaquin Basin. Subsequently, we test the model against two independent albitization trends, one from the Texas Gulf Coast basin and one from the Denver Basin of Colorado. Our results indicate that albitization in all three basins can be fit by an *E*~*a*~ of 68 ± 4 kJ/mole and *A* of (6.5 ± 0.5) × 10^3^ 1/cm^2^ Ma. The rate dependence on temperature is consistent with experimental values for albite crystal growth and with empirically derived precipitation rates of other diagenetic silicates such as illite and quartz. The parameters and fit suggest that albitization can be modeled as a surface controlled reaction, primarily dependent on temperature.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".