© 2014 AAG/The Geological Society of London Evaluation of portable X-ray fluorescence (pXRF) in exploration and mining: Phase 1, control reference materials
Bibliographic record
Abstract
ABstRACt: This paper describes a project sponsored by the Canadian Mining Industry Research Organisation (CAMIRO) to evaluate the strengths and weaknesses of portable XRF for use in mineral exploration and mining and to develop best-prac-tice protocols in the analysis of rocks, soils, sediments and drill-core. Phase I focussed on the analysis of pulp control reference materials (CRMs) to determine the figures of merit, principally accuracy and precision, of the technique before introducing the confounding parameters associated with in-situ analysis such as heterogeneity, particle size and moisture. Five instruments (three handheld and two portable benchtop) from three manu-facturers were used to carry out replicate analyses (n = 10) of a diverse suite of 41 CRMs, from barren granites, through soils and sediments, to ores. Standard factory calibration, in mining and soil modes, was used. The performance of the instruments was evaluated using x-y plots of results versus established element concentrations for the CRMs and the values of goodness of fit (r2), slope and intercept documented for both full and restricted concentration ranges.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.092 | 0.042 |
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".