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Record W1979492174 · doi:10.1039/b303355d

Direct multielemental analysis of human serum by ICP-MS with on-line standard addition using flow injection

2003· article· en· W1979492174 on OpenAlexaff
Chao-Yang Huang, Diane Beauchemin

Bibliographic record

VenueJournal of Analytical Atomic Spectrometry · 2003
Typearticle
Languageen
FieldChemistry
TopicAnalytical chemistry methods development
Canadian institutionsQueen's University
Fundersnot available
KeywordsFlow injection analysisAnalyteChemistryChromatographyAnalytical Chemistry (journal)Inductively coupled plasma mass spectrometryCertified reference materialsDilutionStandard additionStandard solutionMass spectrometrySample preparationSample (material)Detection limit

Abstract

fetched live from OpenAlex

A simple method where on-line standard addition is performed using flow injection was applied to the direct analysis of human serum by inductively coupled plasma mass spectrometry (ICP-MS). The method involves the injection of 50 μL aliquots of sample into two carriers: 1% HNO3 and a standard solution in 1% HNO3 whose analyte concentration is greater than that in the sample. Because flow injection is used, no sample pretreatment (such as sample dilution or the addition of surfactant or internal standard) is needed, which minimizes sample contamination. Seronorm™ reference human serum was analyzed. Results in good agreement with the certified values were obtained for Al, Mn, Fe, Co, Cu and Zn.

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 categoriesMeta-epidemiology (narrow), Insufficient 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 score0.106
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.024
GPT teacher head0.314
Teacher spread0.290 · 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

Citations34
Published2003
Admission routes1
Has abstractyes

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