The role of ICP-MS in inorganic chemical metrology
Bibliographic record
Abstract
Abstract ICP-MS has played a key role in inorganic chemical metrology for 25 years, from the 1993 CIPM feasibility study which led to establishment of the CCQM. Since that time, the Inorganic Analysis Working Group of the CCQM has organised 56 international comparisons involving measurements by ICP-MS and, in a recent comparison, 16 different national institutes submitted their results using the technique. Metrological applications of ICP-MS currently address an enormous range of measurements using a wide variety of instrumentation, calibration strategies and methodologies. This review provides an overview of the ICP-MS field with an emphasis on developments which are of particular relevance to chemical metrology. Examples from CCQM comparisons and the services available from the participants are used to illustrate how the capability and scope of ICP-MS methods have expanded far beyond the expectations of 1993. This is due in part to the research and development programmes of the national institutes which participate in the CCQM. They have played a key role in advancing new instrumentation and applications for elemental analysis, isotope dilution mass spectrometry, determination of isotopic ratio or composition, and speciation of organometallic compounds. These developments are continuing today, as demonstrated by work in new fields such as heteroatom quantitation of proteins, characterisation and counting of nanoparticles using spICP-MS, and LA-ICP-MS analysis of solid materials.
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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 | 0.015 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".