Mineral–Fluid Interaction in the Lungs: Insights From Reaction-Path Modeling
Bibliographic record
Abstract
Thermodynamic modeling, in conjunction with available kinetic information, has been employed to investigate the fate of chrysotile and tremolite in the human lung. In particular, we focus on mineral-fluid reactions using techniques borrowed from geochemistry, including calculation of saturation indices, activity-ratio phase diagrams, and reaction-path modeling. Saturation index calculations show that fresh lung fluid is undersaturated with respect to both tremolite and chrysotile and these minerals should dissolve, in accordance with conclusions from previous work described in the literature. Modeling of reaction paths in both closed and open systems confirms previous suggestions that chrysotile dissolves faster than tremolite in lung fluid, which offers an explanation for the apparent increase in tremolite/chrysotile ratios in lungs of miners and millers over time. However, examination of activity-ratio phase diagrams and reaction-path model calculations raises the possibility not only that minerals dissolve congruently in lung fluid, but that secondary minerals such as talc or various Ca-Mg carbonates might potentially form in lung fluid as asbestiform minerals dissolve.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".