Neutron Activation Analysis, Atomic Absorption and X‐Ray Fluorescence Spectrometry Review for 2006–2007
Bibliographic record
Abstract
These mature analytical techniques do not show any change in publication level from the previous two years and AAS remains dominant in terms of the number of publications. The last two years have seen fewer technical improvements than in the previous review period. Some interesting papers dealing with uncertainty and quality assurance in INAA were published during 2006–2007. It is suggested that photon activation should be reconsidered because the source of electron accelerators has recently improved. A technique to preconcentrate Se for INAA determination has also been proposed. In the case of AAS, papers on analyte preconcentration continue to be more abundant than those relating to instrumental modification. Sample preparation for AAS is also active and ultrasound‐assisted leaching shows some promising applications. There were an unusual number of reviews concerned with AAS and those important to geological samples are cited here. A technique to preconcentrate Cr in water is presented and a new device to determine As and Se is showing some potential uses. Confocal X‐ray mapping continues to show interesting developments. One group developed a technique to perform XRF inside an oyster and an interesting application of μ‐XRF mapping of sediments is presented. Determination of platinum‐group elements (at μg g1 concentrations) can be carried out very quickly with an improved XRF technique.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.008 |
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".