Reading the mineral record of fluid composition from element partitioning
Bibliographic record
Abstract
Research Article| September 01, 2010 Reading the mineral record of fluid composition from element partitioning Vincent J. van Hinsberg; Vincent J. van Hinsberg * Hydrothermal Geochemistry Group, Department of Earth and Planetary Sciences, McGill University, Montreal, Quebec H3A 2A7, Canada *E-mail: V.J.vanHinsberg@gmx.net. Search for other works by this author on: GSW Google Scholar Artasches A. Migdisov; Artasches A. Migdisov Hydrothermal Geochemistry Group, Department of Earth and Planetary Sciences, McGill University, Montreal, Quebec H3A 2A7, Canada Search for other works by this author on: GSW Google Scholar Anthony E. Williams-Jones Anthony E. Williams-Jones Hydrothermal Geochemistry Group, Department of Earth and Planetary Sciences, McGill University, Montreal, Quebec H3A 2A7, Canada Search for other works by this author on: GSW Google Scholar Geology (2010) 38 (9): 847–850. https://doi.org/10.1130/G31112.1 Article history received: 10 Feb 2010 rev-recd: 16 Apr 2010 accepted: 29 Apr 2010 first online: 09 Mar 2017 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Search Site Citation Vincent J. van Hinsberg, Artasches A. Migdisov, Anthony E. Williams-Jones; Reading the mineral record of fluid composition from element partitioning. Geology 2010;; 38 (9): 847–850. doi: https://doi.org/10.1130/G31112.1 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietyGeology Search Advanced Search 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. You do not have access to this content, please speak to your institutional administrator if you feel you should have access.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".