Advances in ICP-MS technology and the application of multi-element geochemistry to exploration
Bibliographic record
Abstract
There have been several advances in inductively coupled plasma-mass spectrometer (ICP-MS) analytical technologies in the last decade. Collision/reaction cell ICP-MS and triple quadrupole ICP-MS techniques can produce lower detection limits for select elements that experience interferences with a standard quadrupole (e.g. Se and As). Triple quadrupole ICP-MS, in particular, can eliminate virtually all polyatomic or isobaric interferences for highly accurate measurements of some element isotopes systematics that are of great interest in mineral exploration, namely Pb/Pb. Laser ablation ICP-MS has become more popular as an effective analytical tool to measure mineral grain trace elements, which could assist in vectoring to mineralization or exploration drill targets. The ablation of a spot on a Li-borate fused glass disk paired with XRF analysis has also gained popularity as an alternative to total whole rock characterization packages that employ several separate digestions and analytical methods. While there have been several advancements in ICP-MS technologies in exploration geochemistry, they have not been widely accepted or implemented. This slow adaptation could be due to the extended recession in the mining industry between 2012 and 2017. It is also possible that standard ICP-MS data (i.e. no collision/reaction cell) is still fit for purpose. This stands in stark contrast to implementation of ICP-MS in the previous decade (1997–2007), which was transformational for the industry. Consideration of all elements from large multi-element ICP-MS analytical suites for mineral exploration can be an extremely powerful tool in the exploration toolkit. The discovery of the White Gold District, Yukon, is a prime example of how the utilization of soil geochemical data, when plotted spatially, can vector to gold mineralization. The presence of Au + As + Sb soil anomalies were key to delineating mineralization, especially when accompanied by publicly available geological, geographical and geophysical data. Additionally, elements and element ratios not typically considered in Au exploration, including Ni and U, were utilized to determine the lithological and structural controls on mineralization. The availability of multi-element ICP-MS data was also useful in the discovery of the Cascadero Copper Taron Caesium deposit. Ore-grade Cs was discovered only because Cs was included in the multi-element ICP-MS exploration geochemistry suite. Before the availability of ICP-MS, it is unlikely that this deposit would have been discovered. Thematic collection: This article is part of the Exploration 17 collection available at: https://www.lyellcollection.org/cc/exploration-17
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".