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Neutron Activation Analysis, Atomic Absorption and X‐Ray Fluorescence Spectrometry Review for 2006–2007

2008· article· en· W2143006055 on OpenAlexaff
L. Paul Bédard

Bibliographic record

VenueGeostandards and Geoanalytical Research · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear Physics and Applications
Canadian institutionsUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsNeutron activation analysisX-ray fluorescenceAnalyteAtomic absorption spectroscopyChemistryAnalytical Chemistry (journal)RadiochemistryEnvironmental chemistryFluorescenceChromatographyPhysics

Abstract

fetched live from OpenAlex

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 g 1 concentrations) can be carried out very quickly with an improved XRF technique.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.618
Threshold uncertainty score0.484

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.038
GPT teacher head0.369
Teacher spread0.331 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2008
Admission routes1
Has abstractyes

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