GGR Biennial Review: Atomic Absorption, Inductively Coupled Plasma‐Atomic Emission Spectrometry, Neutron Activation Analysis and X‐Ray Fluorescence Spectrometry Review for 2008–2009
Bibliographic record
Abstract
This review describes developments major and in trace element determination using atomic absorption spectroscopy (AAS), inductively coupled plasma‐atomic emission spectrometry (ICP‐AES), instrumental neutron activation analysis (INAA), and X‐ray fluorescence (XRF) spectrometry that were reported in 2008 and 2009. Publication levels were comparable to those of previous years, except for XRF which showed an increase in the number of articles published in the past 2 years. In terms of number of publications and impact, the most active field was AAS, while INAA was the least active. As expected for well‐established and mature methods, novel developments for all four analytical techniques were relatively sparse. For AAS, the most notable publications concerned developments in sample introduction, particularly focussing on solid samples, increasing analyte sensitivity, and higher sample throughput. For ICP‐AES, publication of developments in sample introduction, remediation of matrix effects and calibration continues. Compared with past years, there was a clear focus on sample preconcentration methods, but very few publications reporting new hyphenated speciation methods. For INAA, there were several publications exploring the accuracy and robustness of the method, as well as the requirements for INAA to meet criteria for a primary method of measurement. Two other related techniques, delayed neutron activation analysis, and prompt gamma activation analysis, were also described. Hyphenated XRF techniques showed interesting developments in enabling XRF and XRD analysis on the same spot, and further work characterising and calibrating three‐dimensional micro‐XRF shows promising results for investigating sample heterogeneity.
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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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.033 | 0.026 |
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".