Uranium, thorium, and potassium analyses using pXRF spectrometry
Bibliographic record
Abstract
The application of portable XRF spectrometry (pXRF) for determining concentrations of uranium (U), thorium (Th) and potassium (K) was evaluated using a combination of 12 Certified Reference Materials, 17 Standard Reference Materials, and 25 rock samples collected from areas of known U occurrences or mineralization. Samples were analysed by pXRF in Soil, Mining Cu/Zn and Mining Ta/Hf modes. Resulting pXRF data were compared to published recommended values, obtained by total or near total digestion methods with ICP-MS and ICP-OES analysis. Results for pXRF show a linear relationship, for thorium, potassium, and uranium (<5000 ppm U) as compared to the recommended concentrations. However, above 5000 ppm U, pXRF results show an exponential relationship with under reporting of pXRF concentrations compared to recommended values. Accuracy of the data can be improved by post-analysis correction using linear regression equations for potassium and thorium, and samples with <5000 ppm uranium; an exponential correction curve is required at >5000 ppm U. In addition, pXRF analyses of samples with high concentrations of uranium (e.g. >1 wt.% U) significantly over-estimated potassium contents as compared to the published values, indicating interference between the two elements not calibrated by the manufacturer software.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".