Advances in the use of isotopes in geochemical exploration: instrumentation and applications in understanding geochemical processes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Among the emerging techniques to detect the real footprint of buried ore deposits is isotope tracing. Novel and automated preparation systems such as continuous flow isotope ratio mass spectrometry, off-axis integrated cavity output spectroscopy for isotopic compositions of selected molecules, multi-collector inductively coupled-plasma mass spectrometry (ICP-MS), triple quadrupole ICP-MS, laser ablation ICP-MS, and a multitude of inline preparation systems have facilitated the use of isotopes as tracers in mineral exploration, as costs for isotope analyses have decreased and the time required for the analyses has improved. In addition, the isotope systems being used have expanded beyond the traditional light stable and Pb isotopes to include a multitude of elements that behave differently during processes that promote the mobilization of elements during both primary and secondary dispersion. Isotopes are also being used to understand barren areas that lack a critical process to form an ore deposit and to reveal precise redox mechanisms. The goal is to be able to use isotopes to reflect a definitive process that occurs in association with the deposit and not in barren systems, and then to relate these to something that is easier to measure, namely elemental concentrations. As new generations of exploration and environmental scientists are becoming more comfortable with the application of isotopes to effectively trace processes involved in geoscience, and new technologies for rapid and inexpensive analyses of isotopes are continually being developed, novel applications of isotope tracing are becoming more mainstream. Thematic collection: This article is part of the Exploration 17 collection available at: https://www.lyellcollection.org/cc/exploration-17
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it