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Record W1986465756 · doi:10.1039/b007518n

Application of column switching in high-performance liquid chromatography with on-line thermo-oxidation and detection by HG-AAS and HG-AFS for the analysis of organoarsenical species in seafood samples

2001· article· en· W1986465756 on OpenAlexaboutno aff
M. A. Súñer, Vicenta Devesa, Ociel Muñoz, Dinoraz Vélez, R. Montoro

Bibliographic record

VenueJournal of Analytical Atomic Spectrometry · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicArsenic contamination and mitigation
Canadian institutionsnot available
Fundersnot available
KeywordsArsenobetaineChemistryCertified reference materialsChromatographyArsenateDetection limitAtomic absorption spectroscopyArseniteArsenicElutionAnalytical Chemistry (journal)

Abstract

fetched live from OpenAlex

A column-switching system between a cation-exchange column (PRP-X200) and an anion-exchange column (PRP-X100) was used for separation of eight arsenic species. The sample was injected on the PRP-X200 column and the species eluted in the void volume of that column [arsenite (AsIII), arsenate (AsV), monomethylarsonic acid (MMA), dimethylarsinic acid (DMA) and arsenobetaine (AB)] were transferred to the PRP-X100 column and, after separation, were thermo-oxidized on-line and detected by hydride generation (HG) atomic absorption spectrometry (AAS). The species initially retained in the PRP-X200 column were subsequently separated in that column, thermo-oxidized on-line and detected by HG atomic fluorescence spectrometry (AFS). The organoarsenical species present in natural seafood products were extracted with methanol–water and quantified using the proposed method. The analytical features of the method are reported. The highest limit of detection (LOD) for the sample was obtained for AB [3.6 ng g−1, dry mass (dm)], whereas TMAO and DMA gave the lowest LOD (0.9 ng g−1 dm). For all species the methodology developed provides optimum precision, ranging from 1 to 12%, and the recovery percentage was greater than 95% for all species. The method was applied to the following certified reference materials: CRM 627 (Tuna fish tissue, Institute for Reference Materials and Measurements, IRMM), DORM-2 (Dogfish muscle, National Research Council of Canada, NRCC), TORT-2 (Lobster hepatopancreas, NRCC) and NFA-Shrimp and NFA-Plaice (National Food Agency of Denmark). Only CRM 627 is certified for arsenic species (AB and DMA), and the contents obtained for these species were compared with the certified values. The contents of the other arsenic species present in CRM 627 and the species in the other reference materials were compared with the data reported by other authors.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.008
GPT teacher head0.228
Teacher spread0.220 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations53
Published2001
Admission routes1
Has abstractyes

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