Determination of Trace Elements in BCS CRM 313/1 (BAS) and NIST SRM 1830 by Inductively Coupled Plasma‐Mass Spectrometry and Instrumental Neutron Activation Analysis
Bibliographic record
Abstract
In the past, there has been little interest in the trace element characteristics of quartz, and in consequence little activity in the trace element characteristics of reference materials with high silicon content. The main purpose of this paper is to contribute to the characterisation of two international certified reference materials, BCS 313/1 from the Bureau of Analysed Samples, (BAS), UK and SRM 1830 from the National Institute of Standards and Technology (NIST), USA. BCS 313/1 was analysed by laser ablation inductively coupled plasma‐mass spectrometry (LA‐ICP‐MS), solution ICP‐MS and instrumental neutron activation analysis (INAA). NIST SRM 1830 was analysed by LA‐ICP‐MS and INAA. Analytical results are reported for more than forty elements, most of them for the first time. For most elements, the results obtained by the different methods agree within 15 % relative. The recent, heightened interest in quartz and in particular the precise determination of trace0element contents in natural quartz samples requires the use of well characterised reference materials such as BCS 313/1 and SRM 1830, to which this study is designed to contribute.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".