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Trends in Analytical Developments and Earth Science Applications in LA‐ICP‐MS and LA‐MC‐ICP‐MS for 2004 and 2005

2006· article· en· W2076936093 on OpenAlexaff
Paul Sylvester

Bibliographic record

VenueGeostandards and Geoanalytical Research · 2006
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsInductively coupled plasma mass spectrometryLaser ablationAnalytical Chemistry (journal)MicroanalysisIsotope dilutionElemental analysisMass spectrometryChemistryLaserMineralogyMaterials scienceEnvironmental chemistryPhysicsOptics

Abstract

fetched live from OpenAlex

This review of laser ablation‐inductively coupled plasma‐mass spectrometry includes research that employed quadrupole instruments, and single‐collector and multicollector magnetic sector field instruments. The most important trend in 2004–2005 was the growing appreciation that small matrix effects in LA‐(MC)‐ICP‐MS need to be addressed in order to produce highly precise and accurate data by the method. The issue is most acute for isotope ratio measurements that require standard‐sample‐standard bracketing but can also be important for certain elemental analysis. Matrix‐dependent elemental and isotopic fractionations were studied from the standpoint of laser‐sample interactions and the behaviour of laser‐generated particles in the ablation cell, transfer tubing and ICP torch. Innovations in LA‐(MC)‐ICP‐MS involved signal smoothing, in torch laser ablation, on‐line isotope dilution and molecular oxide monitoring. Other important research was carried out on the calibration and homogeneity of various reference materials; and the exploration of mature ( in situ U‐Pb geochronology) and emerging (apatite fission‐track chronometry, U‐Th/He thermochronology, boron/strontium/uranium‐series isotopic microanalysis) applications in the Earth sciences.

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)0.003
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.950

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.002
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 head0.028
GPT teacher head0.331
Teacher spread0.302 · 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 designObservational
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

Citations17
Published2006
Admission routes1
Has abstractyes

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