Suitability of Au<scp>RM</scp>2 as a Reference Material for Trace Element Microanalysis of Native Gold
Bibliographic record
Abstract
Microanalysis of native gold specimens has been hampered by the lack of a suitable reference material (RM) known to be sufficiently homogeneous at the scale of microanalytical sampling. The suitability of gold reference material AuRM2 for microanalysis was assessed. This RM was created for bulk analysis of refined gold and was only certified for homogeneity at the bulk scale. However, it contains trace elements in appropriate mass fraction ranges for analysis of native gold. This study was not intended to provide alternative mass fractions from the original certified values, only to assess its suitability for microanalytical methods. Micro‐scale (~ 3.4 μg sample mass) heterogeneity was calculated from measurement repeatability of LA‐ICP‐MS analyses of AuRM2 by factoring in signal (represented by counting statistics) and instrument set‐up‐specific variability (determined using measurement variability of a reference material known to be homogeneous). Elements determined to be homogeneous or to have minor heterogeneity (< 10% calculated heterogeneity RSD) are Mg, Al, Ti, Fe, Ni, Cu, Zn, Se, Rh, Sn, Sb, Pt and Pb. Elements with moderate heterogeneity (10–20% heterogeneity RSD) are: Mn, As, Pd, Te and Bi. Correlation of element mass fractions indicates that micro‐scale inclusions of chalcophile‐rich phases along grain boundaries may be responsible for some of the chemical heterogeneity. However, the level of heterogeneity is statistically negligible compared with the ranges of chemical signatures observed in sample populations of native gold. Therefore, AuRM2 is shown to be sufficiently homogenous at a micro‐scale for use as a RM for microanalysis of native gold.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".