Reading the mineral record of fluid composition from element partitioning
Bibliographic record
Abstract
Earth is the "blue planet," with more than 70% of its surface covered in water and the equivalent of up to four oceans of water in its interior. This abundance of water has a profound impact on the processes that shape our planet as well as the development of the organisms that inhabit it. To understand this impact, it is necessary to know the properties and compositions of this fluid. At present, this information is largely unavailable, because direct samples of fluid are rare, especially for early Earth and Earth's interior, and other estimators are semiquantitative, at best. Here we propose a different approach in which the composition of the fluid is reconstructed from that of minerals, based on the characteristic trace element partitioning between minerals and aqueous fluids. We show experimentally that this partitioning is systematic and obeys lattice-strain theory. It depends strongly on element complexation in the fluid, but this dependence is predictable and can be accommodated. Unlike fluids, minerals with preserved compositions are readily available in the geological record, and this approach therefore provides a powerful and widely applicable tool to reconstruct a quantitative record of fluid composition for the full range of Earth environments and for its earliest history. © 2010 Geological Society of America.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.022 | 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 teacher head, 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".