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Record W2080108224 · doi:10.1039/b706954e

Direct multielement determination of human hair by induction-heating electrothermal vaporization with ICP-MS

2007· article· en· W2080108224 on OpenAlexaff
Rebecca Lam, Eric D. Salin

Bibliographic record

VenueJournal of Analytical Atomic Spectrometry · 2007
Typearticle
Languageen
FieldChemistry
TopicAnalytical chemistry methods development
Canadian institutionsMcGill University
Fundersnot available
KeywordsVaporizerChemistryVaporizationAnalyteInductively coupled plasma mass spectrometryAnalytical Chemistry (journal)Detection limitChromatographyHair analysisCalibrationCertified reference materialsMass spectrometry

Abstract

fetched live from OpenAlex

Conventional methods of hair analysis using instruments, such as inductively coupled plasma-mass spectrometry (ICP-MS), typically require a digestion step that has many disadvantages. As an alternative, we report on the application of an induction heating-electrothermal vaporizer (IH-ETV) with ICP-MS detection for direct multielement determination of sub-milligram amounts of solid hair material. As, Cd, Cu, Hg, Pb and Zn were determined using powdered hair standard reference materials (SRMs) with IH-ETV-ICP-MS. Transient profiles reveal that powdered hair SRMs and hair strands have the same analyte signal shapes, while solutions have different shapes. External standards calibration using SRMs gives results that agree with the certified values, with the precision of determination ranging from 9–54%. Absolute detection limits ranged from 0.01–8 ng. These values are sufficiently low that they should allow the determination of metals at natural levels in a single human hair strand.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.144
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.297
Teacher spread0.284 · 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.

Study designBench or experimental
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

Citations19
Published2007
Admission routes1
Has abstractyes

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