Direct analysis of soils by ETV-ICP-AES: a powerful tool for mineral exploration
Bibliographic record
Abstract
A fast method for the direct analysis of soils, namely solid sampling (SS) electrothermal vapourization inductively coupled plasma atomic emission spectrometry (ETV-ICP-AES), was validated through the accurate analysis of a soil standard reference material (SRM) using another soil SRM as a calibration standard and an Ar emission line as internal standard to compensate for sample loading effects on the plasma. Good agreement was obtained between the measured concentrations and certified values according to a Student’s t-test. The validated method was applied to the determination of the distribution of elements in depth profile soil samples from across the Talbot Lake VMS Cu-Zn prospect, in the Flin Flon-Snow Lake terrane, Manitoba, Canada. These profiles revealed that: Zn, P and Ag had anomalously high concentrations at 20–50 cm depth at 400 m, above where the easternmost part of the ore deposit is located along a 0–1000 m sampling line; Cu, Al, Ba, Pb and Hg were concentrated on the surface and at 40-cm depth mostly between 500 and 600 m; and Cl, Br and I were concentrated at depth at 400 m and over all depths at 600 m. As the geochemical anomaly is known to lie from 400 to 600 m, all these elements could be used to locate the ore. Good agreement was obtained with results by ICP mass spectrometry (ICP-MS) following aqua regia (AR) digestion, for those elements that could be determined by ICP-MS. In fact, not only is sample dissolution unnecessary but qualitative analysis by SS-ETV-ICP-AES is sufficient to obtain depth profiles, including for elements like Cl, which cannot be determined when AR is used for digestion.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".