Comparative pXRF and Lab ICP-ES/MS methods for mineral resource assessment, Northwest Territories
Bibliographic record
Abstract
The Geological Survey of Canada undertook a mineral resource assessment for a proposed national park in northern Canada (~ 33,500 km2) spanning the transition from boreal forest to barren lands tundra. Bedrock geology of this region is complex and includes the Archean Slave Craton, the Archean and Paleoproterozoic Rae domain of the Churchill Province, the Paleoproterozoic Thelon and Taltson magmatic-tectonic zones, and the Paleoproterozoic East Arm sedimentary basin. The area has variable mineral potential for lode gold, kimberlite-hosted diamonds, VMS, vein uranium and copper, SEDEX, as well as other deposit types. A comparison of analytical methods was carried out after processing the field collected samples to acquire both the < 2 mm and for the < 0.063 mm size fractions for 241 surficial sediment (till) samples, collected using a 10 x 10 km grid. Analytical methods comprised: 1) aqua regia followed by ICP-MS analysis, 2) 4-acid hot dissolution followed by ICP-ES/MS analysis, 3) lithium metaborate/tetraborate fusion methods followed by ICP-ES for major elements and ICP-MS for trace elements and, 4) portable XRF on dried, non-sieved sediment samples subjected to a granular segregation processing technique (to produce a clay-silt proxy) for seventeen elements (Ba, Ca, Cr, Cu, Fe, K, Mn, Ni, Pb, Rb, Sr, Th, Ti, U, V, Zn, and Zr) Results indicate that pXRF data do not replicate exactly the laboratory 4-acid and fusion data (in terms of precision and accuracy), but the relationship between the datasets is systematic as displayed in x-y scattergrams. Interpolated single element plots indicate that till samples with anomalies of high and low pXRF concentration levels are synonymous with high and low laboratory-based analytical concentration levels, respectively. The pXRF interpolations thus illustrate the regional geochemical trends, and most importantly, the significant geochemical anomalies in the surficial samples. These results indicate that pXRF spectrometry for a subset of elements is comparable to traditional laboratory methods. pXRF spectrometry also provides the benefit of rapid analysis and data acquisition that has a direct influence on real time sampling designs. This information facilitates efficient and cost-effective field projects (i.e. where used to identify regions of interest for high density sampling), and to prioritize samples to be analyzed using traditional geochemical methods. These tactics should increase the efficiency and success of a mineral exploration and/or environmental sampling programs.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 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".